#solving for the null hypothesis and what not. you know

[the-audac-ity]

There are people who follow you, and there are people you follow.

Then there are mutuals. These break down as such: basic mutuals, mutuals you don't know why you're mutuals but there was probably a reason, mutuals you mean to unfollow but haven't yet, mutuals to your sideblog(s), good mutuals, that one mutual, the mutual of my mutual (aka mutual in-laws), ex-mutuals, beloved mutuals, and the beloved mutual. And sometimes, if you're lucky, there's the bestie.

[moralisist]

tutor armin

warnings: x fem reader!, college au, suggestive, lowk long 😭

math has forever been unkind to you. c’s and sometimes d’s would be a regular occurrence with math. you were an a+ student don’t get me wrong but math? it just never made sense.

your teacher tried to help you, but it’d anger her to the point of having to take breaks while teaching you just so she wouldn’t yell at you. how could a straight a student like you not get a concept that’s been taught for months now?

you were in a bind. your gpa would be perfect if it wasn’t for math and you didn’t know who to go to. it was also a bit embarrassing to ask someone else for help. however, your teacher would make sure you’d get the help you needed.

it was the end of a lecture in your statistics class. you were reviewing notes and looking through your text books but you were still so lost. you figured you’d just study more at home and begin to get up from your seat.

��ms. y/n and mr armin, can we chat?” your teacher asks you. you make eye contact with the blondie from across the room who was still packing up his things. you head to your teacher but you can still feel a pair of eyes on you.

“armin, i’d like to ask you for a favor.” your teacher asks him. he smiles. “yes of course, anything miss.” he seemed so polite. and he was quite handsome too. a cute round face with a jawline popping out whenever he clenched his jaw, his cheeks were naturally a bit rose, and short hair that framed his face quite nicely. his attire matched his vibe and it was so put together but clearly not trying too hard. and his eyes-

“so what do you say y/n?” miss asks. you look over to armin who has hopeful eyes. you have no idea what she asked but you decide to go for a safe answer.

“yes.” your teacher giggles. “well it’s settled! tomorrow and after every lesson, armin will tutor you!” your eyes widen just a bit while looking back at armin who was already looking at you. he smiles kindly like he always does.

“does 3 work for u tommorow?” he asks you. “yeah 3 is good.” you smile back.

it’s the next day and you’re sitting at your desk, taking notes but can’t help but glance at armin every once in a while. how come you never really noticed him? was he sitting here all this time? so many questions you had to ask and you were hopeful you’d get them answered by today.

“y/n!” armin walks over to you when it’s the end of your lesson. “where do you wanna study?” it was weird. it’s almost like he was excited.

“we can study in my dorm if you’re okay with that. i got some snacks yesterday too that we can share.” you say hoping it didn’t sound too flirtatious. “sounds great.” you both smile at each other, walking and making polite small talk on the way to your dorm.

you guys are sitting on your floor while he’s talking to you about null and alternative hypothesis. for the first time in a long time, things were starting to come together. armin made sure to go back to the basics and reviewed it with you so you could grasp it and he made sure to prepare you for the upcoming test. armin could see you becoming more confident in your answers and you were solving problems without his help.

you both decide to take a break and you guys are laying on your floor, talking each others ears off. he talked about his interests in books and history, while you shared about how hard you had to work in school and what arts you were into. armin loved talking to you about these things, the things that made him, him. he could never go to his friends about this stuff, it was too sappy for them.

as hours go by, you guys are indeed sharing the snacks you offered him and you and armin are already so close. you both are talking about deep desires and wants, while sharing your secrets, free of judgement. a comfortable silence falls between you two.

“i’m proud of you y/n. you did a really good job today.” you both are on your bed at this point, your guys’ body heat meshing although you guys are just next to each other. “thank you. and thank you for all your help armin. it means everything to me.” you look at him with bright eyes, your skin heating. armin stares at you again with those kind eyes.

he holds a part of your face in his hand, silently asking for permission. instead of waiting, you grab his face gently and kiss him. the kiss is soft and sweet. it’s filled with curiosity as your toungues are exploring each other and seeing what the other likes.

it wasn’t armins first kiss but you took control of the kiss as if it was. you were a fire he wasn’t used to but he loved it. it was so thrilling to him. you straddled his waist while continuing to attack his lips. you were getting more confident by the second seeing the way armin melted underneath you. it was all too much but the sensation was nothing like you’ve felt before. his kisses were comforting, the way he’d give you a peck on the lips when you guys would slow down and then he’d dive for more. you both loved everything about it.

armin pulls away from you, looking incredibly disheveled. “y/n, i really like you. but before we go further i wanna take you on a proper date, is that okay?” you smile at him and wrap your arms around his neck, laying on him. “that’s more than okay. i’d love that.”

armin had been tutoring you for the last couple days before the big test. you both were getting closer and closer as the days went by, learning more than you thought you could learn about him in such a short time.

it was finally the day of the test and you and armin were walking in together, it becoming your usual routine now. he stops you when you guys approach nearby because he can tell you’re nervous. he was an observant one, you noticed.

“don’t be nervous y/n. you’re gonna do great and you studied so hard and for so long.” you sigh, “okay and what if i don’t do well?”

“i’ll be there to help you study and we can cover the basics all over again if you’d like us to. i’m here for when you need me, and you’re gonna do great so don’t think like that.” he gives you a kiss on the cheek and then on the lips. “now let’s go in.” he leads you by holding your lower back and rubbing ur back up and down.

you finish your test and hand it in while your teacher looks at it briefly. “i haven’t graded it yet y/n, but it’s looking good. keep up the good work with armin.” you smile a big toothed smile while saying thank you and walk over to armin who finished his test a bit before you. you guys head out the class and you jump into his arms while smiling and talking about the fact armin might’ve landed you an a in math.

“you did all that work yourself! i’m so proud of you.” he hugs you even tighter. “i think you deserve a nice dinner huh?” he grips ur waist while he pulls you away from him to see your face. your smile was infectious.

“come, i’ll take you to your dorm so you can get ready. my smart girl needs all the time she wants so we can go later tonight, let’s say 6? i’ll come get you.” he grips your hand while walking to your dorm.

what would you have done without your super smart, super cute, and super dorky tutor of a future boyfriend?

a/n: requests r open!

[taweretsdagger]

jack's need to find the answer vs. juliet's need to look over the edge

lost's tragic, (probably) autistic doctors, part three

alright gang, let's put some analysis weight behind the word "tragic" in this series title :')

in part one, we discussed several similarities between jack and juliet through the lens of some autistic traits, and in part two we discussed how gender presentation/societal expectations could cause other autistic traits to show up differently in the two characters.

i don't have much more autism-specific analysis to add here, but will reiterate two points i brought up in parts one and two as they'll also be useful for understanding how these characters reach their respective tragic ends:

the metaphor of viewing jack and juliet's relationship like two mirrors facing each other

jack and juliet's shared desire/struggle to find belonging

so, first off: titles. the title of this installment, the title of this series. the title of "doctor." this is an essential title for both jack and juliet, and i do mean "essential" quite literally. this title drives not only their careers, but their personalities, their strengths and weaknesses, their problem-solving approaches, and so on.

their very essence is encapsulated in this title, but in the end, that doesn't tell us much about them on its own. we use the term "doctor" to refer to all manner of career pathways and advanced degrees. in her infinite wisdom, juliet makes this point clear when she counters being referred to as a doctor by saying "[she's] really more of a researcher."

so what's the difference, between a (medical) doctor and a researcher? despite all the possible implications of referring to someone with the title of doctor, i'd imagine most people would think of a medical doctor when i use that word. so let's look to the dictionary to understand the former.

while the definition of "doctor" sounds a bit nefarious...

(verb) change the content or appearance of (a document or picture) in order to deceive; falsify.

...we can apply a more neutral connotation to understand this profession as one of diagnosing, and ultimately fixing. making right.

sound like anyone we know?

meanwhile, research takes a different mindset. every null hypothesis you prove false leads to several new alternative hypotheses. you're never really done, because there isn't "one answer" in research. it takes keen observation, and intellectual stamina/humility, and a willingness to try. a willingness to ask "why," rather than to solely insist on understanding "how."

in part two, i discussed juliet's pattern of impulsive behavior (such as chugging the juice richard gives her at the airport) in the context of autistic meltdowns. i also think this tendency is what makes her such a good researcher. while on the surface juliet might seem like an obvious "woman of science," she is clearly willing and able to take things on faith. this also differentiates her from jack as a character; despite their many similarities, juliet does not possess jack's need to understand or identify the answer.

in fact, in the flashback scene we get of juliet as a child in the season five finale, she makes the opposite claim very explicitly:

"i don't want to understand!"

as two of my favorite juliet understanders (hehe) (@lost-inanotherlife and @ginawankenobi) have pointed out, there is also a gendered/self-deprecating element to the way juliet's career is introduced to us. being a surgeon isn't "superior" to being a researcher; both are necessary roles in the medical sciences and come with their own difficulties. but more societal reverence is generally ascribed to the practice of surgery, and it's a role people might be more likely to associate with traits like leadership and strength, at least as compared to the slower, quieter, messier practice of research.

"i'm not a leader, mr. alpert; i'm a mess."

we left off part two with juliet just having displayed some excellent leadership skills... notably, while performing surgery on jack. by the end of season four, we'll see jack finally getting rescued (with only five of his people with him), and juliet missing out on yet another chance to escape the island. we see jack failing to live up to the promise he made her, and we already know that this failure (among other things) is going to drive him into a deep depression within a few years.

meanwhile, juliet gets a new life on the island, making good on the bad hand she got dealt. she has friends, a job free from the baggage of her traumatic experiences with ed and ben, and, as i mentioned in part two, it seems likely that as sawyer ascends to a position of leadership within the dharma initiative, juliet would operate as his advisor and confidant (like many women do with their male, leader partners in societies where women cannot occupy leadership positions themselves, which seems to be the case for dharma). she has experience living in the barracks and an insider's understanding of the "hostiles," both of which would constitute valuable insight for dharma's head of security.

as discussed in part one, jack's projection of his desire to belong onto juliet is ultimately what enables his (woefully brief) "golden age" as the crash survivors' leader at the end of season three. however, juliet's ability to find belonging and esteem within dharma is not reliant on jack or any projection of her own issues onto him. AND, jack is absolutely Going Through It back in the real world, once more projecting his desire to return to the island ONTO juliet as a sort of remix of his need to save her (which of course, is really jack's need to save himself). but this time, juliet doesn't need or want saving. our two mirrors are out of balance. when they reunite, that imbalance presents as tension that has nowhere to climb but up.

as soon as the gang returns, juliet clocks where things are going. this is shown largely to us through the scene in which she's watching jack and kate out the window and sawyer asks her "what's on TV?"

i won't spend too much time discussing the significance of this scene overall, but would be remiss not to reference this incredible series for those who yearn to sink their teeth into it as much as i do.

for the purposes of this post, what's most crucial in understanding this scene is putting it in context of our mirror metaphor. if our two mirrors are out of balance, maybe all the "meat" of the light and energy that was previously bouncing back and forth between them is starting to coalesce within jack, giving juliet an opportunity to become a spectator to a dynamic in which she used to be a more active participant. (also, what is a television but a "black mirror?")

before long, this tension crashes in the form of our first jack/juliet collision, when she confronts him after he refuses to help save ben and calls out the hypocrisy and projection in his stated reasons for returning to the island.

okay, now let's move on to the bomb :')

the period between the scene of juliet's confrontation of jack and the moment when she decides she's going to help him detonate the hydrogen bomb is difficult to analyze, since like most people i really didn't appreciate the return of a love triangle with kate. three years have passed, and these are grown adults. it's just really difficult for me to buy as a viewer, and the lost writers themselves have admitted it wasn't their best moment. but i'm going to give the canon events as much credence as i can within the analytical framework we've established in this series.

juliet is insecure, and prone to self-destruction when things are getting out of hand. we know this. we also know that she can see the beginning of the end of the life she and sawyer have built in dharma. rather than her next "meltdown" coming about specifically due to her jealousy of kate, i think it's more likely a result of losing so much control and agency so quickly. i think she's also engaging in a fair bit of projection/externalization of that loss of control onto sawyer, sort of like her own version of what jack did when he externalized his fear of the appendectomy onto kate in season four.

daniel is the physicist in the group, but his reasoning for detonating the bomb really has nothing to do with science at all. instead, his "variable" theory is wound up entirely in his grief over losing charlotte. but i imagine in part based on the credibility of his expertise, jack is able to latch onto the idea of the bomb as a "scientific" solution to all his problems. hit the reset button, and try again. simple enough! for juliet though, i don't think precise reasoning and rational defense of the bomb as a solution is a necessary part of her decision equation. it's another moment of her self-destructive impulsivity colliding with the island's forces and will, just like when she chugged the juice.

once juliet changes her mind about the bomb, our mirrors appear to be back in sync. however, the tension is still there, and still plenty dangerous--even explosive. *especially* when you enter a hydrogen bomb into the equation (even just the core). at least one of them is going to have to die in the process; there's just way too much potential energy and it's resonating between them too rapidly.

two things are particularly interesting to me about how the incident itself plays out: for one, juliet is DRAGGED over the edge of the swan abyss, but in the end she DECIDES to let go of sawyer's hand and let herself fall. and then when she wakes up underground later, she DECIDES to detonate the bomb herself.

for those first few dragging moments, all her morbid curiosity comes back to haunt her, and i'm sure she saw every juice-chugging-adjacent moment of her life flashed before her eyes. but she still accepts her fate, and still uses the last remnants of her physical strength to see through their mission to the bitter end.

secondly, jack ends up having to take the bomb detonation on faith. he drops it down the chasm, but everything that happens after that is out of his hands. he had no idea whether it had detonated on impact, and would have had no idea that their fate was left up to juliet if she hadn't lived long enough to tell sawyer what happened.

jack begins the experiment with the bomb, but juliet becomes the catalyst necessary to finish it. in doing so, she also becomes the catalyst of jack's transformation from a man of science into a man of faith, since he HAS to let go of her. he failed to save her multiple times, and then he got her killed. that's that. there's nothing he can do to change it. and at the same time, he's lost his second mirror. he can't project onto juliet, he can't project onto kate, he can't project onto anyone. he has to embody all the energy that once had been shared--however unevenly--and i'd argue that this is a key element in jack learning that he does, indeed, have what it takes. that's a lot to hold, maybe more than he's ever tried to hold before.

(one thing about juliet, she had what it took. imo, you don't smash a hydrogen bomb with a fucking rock if you don't have what it takes.)

jack doesn't die during the incident, but in a way he's been dead ever since he got up on that bridge. in part, the bomb was another manifestation of his suicidality. the cataclysm of juliet's demise gives jack a reason to stay alive, at least long enough to accept the role as the island's protector, kill the man in black (with a crucial assist from kate), and halt the island's destruction. he ends up underground just like juliet, doomed just like juliet, but his experience of that doom couldn't be more different. he's laughing, bathed in incandescent light, and learning something new about himself.

and the parallel differences don't end there: juliet dies in sawyer's arms, comforted by the belonging she craved for so long and finally found, even if only for a short while. meanwhile, jack dies alone (well, almost... thank god for vincent <3). both of them go out looking content, but their contentedness is sad to us for disparate reasons.

so, we could call all of season six a last gasp gifted to jack by juliet, but within that series of events there's another, subtler last gasp for which he has her to thank.

to close this series out, let's talk about our beloved appendectomy, one more time.

all things considered, jack's a pretty lucky duck. he gets a life-saving 2-for-1 on this surgery. REALLY not a bad deal, for a procedure performed on the beach by torchlight, by someone who's "really more of a researcher."

not only does juliet save jack's life by performing the surgery itself in season four, but the absence of jack's appendix is what allows him to survive long enough after being stabbed by the man in black to save the island (and, therefore, the world). otherwise, he would've bled out too quickly, and everything would've fallen into ruin.

that pesky little vestigial organ almost killed our hero twice, and both close calls are staved off by the surgical skills of a woman who doesn't even totally consider herself a doctor, let alone a leader! i mean, talk about misplaced insecurity! when they meet up in that church i very much hope that jack took the opportunity to tell juliet how much of a hero she was in her own right, and how little he could've accomplished without her expertise and determination. and in case he didn't, I'M gonna do a little projecting of my own and beam that message into the universe for juliet to pick up on!!!

thank you so so much for reading along everyone! :) i hope you enjoyed this extended look into the minds and lives of two very fucked-up people who are very destined to be divorced from one another <33

(speaking of, let me tag in what i consider the spiritual successor to this series, or @obsessivedaydreamer's jack/juliet flash-sideways fic, "Across Our Great Divide." a true masterpiece, and very necessary reading to understand our repo divorcees!!!!)

[mvishnukumar]

How should I prepare for statistics questions for a data science interview? What topics should I brush up on?

Hi,

Preparing for statistics questions in a data science interview involves reviewing key concepts and practicing problem-solving. Here’s how you can effectively prepare:

1. Review Core Statistical Concepts:

Descriptive Statistics: Understand measures of central tendency (mean, median, mode) and measures of dispersion (variance, standard deviation, range). Be able to interpret these metrics and their implications for data analysis.

Probability: Brush up on basic probability concepts, including probability distributions (normal, binomial, Poisson), and the laws of probability. Familiarize yourself with concepts such as conditional probability and Bayes' theorem.

2. Study Hypothesis Testing:

Null and Alternative Hypotheses: Understand how to formulate and test hypotheses. Know the difference between null and alternative hypotheses and how to interpret p-values.

Types of Tests: Review common statistical tests such as t-tests, chi-square tests, ANOVA, and their applications. Understand when and how to use these tests based on the data and research questions.

3. Learn about Regression Analysis:

Linear Regression: Review the principles of linear regression, including the assumptions, interpretation of coefficients, and how to evaluate model performance (e.g., R-squared, adjusted R-squared).

Logistic Regression: Understand logistic regression for binary outcomes, including the interpretation of odds ratios and the application of the model to classification problems.

4. Explore Statistical Modeling:

Model Assumptions: Be familiar with the assumptions underlying various statistical models and how to check for violations.

Model Selection: Understand concepts such as overfitting, underfitting, and cross-validation. Know how to select and validate models based on performance metrics.

5. Practice Problem-Solving:

Sample Problems: Work through practice problems and case studies that involve statistical analysis. This can help reinforce your understanding and improve your problem-solving skills.

Online Resources: Use online platforms like lejhro, Coursera, or DataCamp to practice statistics problems and concepts.

6. Communicate Statistical Findings:

Interpretation: Practice explaining statistical results clearly and concisely. Be prepared to discuss how statistical findings inform decisions and what actions might be taken based on the results.

7. Review Past Projects:

Project Insights: Be ready to discuss statistical methods used in your previous projects. Highlight how you applied statistical techniques to analyze data and solve problems.

By focusing on these areas, you can prepare effectively for statistics questions in a data science interview and demonstrate your analytical capabilities with confidence.

[crzmbbb]

Essential Things for Entrepreneurship

An entrepreneur is someone who pays great attention to his surroundings, constantly evaluates them, and, when he sees a chance for success or a chance to make a difference, he turns it into a business. That is how our team came up with a product that we showed a few days ago. We studied the challenges that exist in several areas, such as agriculture, education, and medicine, and acquired information by interviewing some people who were informed about those disciplines. After obtaining the information needed to create a mock-up prototype solution, we construct hypotheses that we can use to create this prototype solution. The null hypothesis states that the product's quality and purpose are effective in increasing its profitability and price value perception, whereas the alternative hypothesis states that the product's quality and purpose are ineffective in increasing its profitability and price value perception.

Finding a person to interview is one of the most difficult yet crucial aspects of creating a mock-up prototype product or service. It is frequently linked to the interviewees' physical location, availability, and susceptibility. Their voluntary cooperation was added in the hopes that it would offer them direct assistance or, in the long run, ameliorate the problem in the fields they are in, and only a few would participate if they could identify and appreciate its validity and importance. We chose and produced the following questions because we don't know what business to start or what product to build yet. These are the following:

What issues do you face on a daily basis?

What issues remain to be addressed in agriculture, medicine, and education?

What is the current market demand for products as a consumer?

What elements are most essential to you when determining whether to buy from an emerging business?

Do you have any product recommendations based on your evaluation of the challenges experienced in the fields?

We gathered all of the information we had obtained after the interview. We were able to interview 55 biology students in total, and we concluded that the majority of the interviewees agreed and stated that most of the problems or issues that they had encountered could be found in organizing files, and they proposed a website to solve some issues in the said field. certain people also bring up certain current situations, such as sexual harassment, theft, and kidnapping. Others dealt with agriculture. However, my team and I have opted to focus on the education industry because it has the majority. We've decided to create a website. BioEduSphere.com is the domain name we chose. This website focuses solely to the demands of college biology students, and it provides unrivaled benefits.

This week, we studied how to spot possibilities, perform market research, plan efficiently, and recognize the value of passion and purpose. We have listed other things to think about when developing a product, such as distinctiveness, good marketing, start-up costs or capital, and profit.

[max1461]

Ok, I have a scenario I want to model probabilistically, and ideally do hypothesis testing and so forth on, but I'm not exactly sure how to do it. If anyone could point me to a source which describes how to solve this general sort of problem (or even just give me terms to google), that would be very helpful. I want to be able to solve problems like this generally, not just this specific one. Ok, here goes:

Ok, so basically... I have a hypothesis H, which makes predictions about a data set X. In particular, it makes predictions about two related properties of the data, call those properties P1 and P2. So for any x in X, we might have P1(x) or P2(x) or both or neither, and H makes predictions about which x these properties should hold for. Let's refer to these predictions H1 and H2, respectively. So H1 is trying to predict P1 and H2 is trying to predict P2. There are certain other practical constraints placed on what H1 and H2 can be; they aren't allowed to be arbitrary truth functions but must satisfy additional requirements.

Ok, all good so far. It's easy to do hypothesis testing on H2, because it's easy to calculate what the frequency of P2 should be in the data by pure chance. If H2 does sufficiently better than chance at predicting P2, we can reject this null hypothesis, etc. H1 is a little harder because we don't have a clear prior for when P1 should hold by chance, but don't worry about that yet.

The next part is where I start to get fuzzy on the math. There are basically two aspects of this that I don't know how to handle.

The first part is this: we don't actually have H, we are trying to work backwards to determine whether a sufficient H exists. It's possible that the data are related by nothing but chance. The real hypothesis H' that we are interested in is "a hypothesis H which meets [practical constraints] and which does sufficiently better than chance at predicting the data in fact exists" and the null hypothesis we are trying to reject is "there is no hypothesis H which meets [practical constraints] and which does sufficiently better than chance at predicting the data". So, ok, I am not sure how to go from individual hypothesis testing to testing for the existence of hypotheses.

In the general case my intuition is that this isn't doable, "hypothesis space" is just so big that you can always find one that's better than chance. But in my situation, [practical requirements] are highly restrictive, so in fact the mere existence of a much-better-than-chance model meeting these requirements is surprising. It's actually this that I want to hypothesis test on.

Ok, that's part one of what I don't know how to do. Here's the second, even bigger thing. The two properties P1 and P2 are related to each other in a very specific way. In particular, if P1(x) holds for a given x and the hypothesis H is true, we should expect P2(x) to hold with greater probability. If P2(x) holds for a given x and the hypothesis H is true, we should expect P1(x) to hold with greater probability. If the hypothesis H is not true, we should expect P1 and P2 to be basically unrelated to each other.

In fact, it may not just be P2 which is related to P1 in this way. In the real situation, there is actually a whole set of properties P2,...,Pn that we are trying to predict, and they're all related to P1 like this. So if H is true and P1(x) holds, we should expect to see a greater proportion of P2(x), ..., Pn(x) holding. And the more of P2(x), ..., Pn(x) hold, given H, the more likely it should be that P1(x) holds. If H is false, there should be no relationship. And so, intuitively, we are looking for a collection H2,..., Hn that are heavily "inter-reinforcing", above and beyond what is expected by chance. If H_i and H_j are both true of x for a lot of the same x, then H_i and H_j are sort of providing evidence for each other. If a big collection H2,..., Hn exists that all provide evidence for each other, that is strong evidence that a hypothesis H satisfying our requirements exists. If no H2,..., Hn can be found, we fail to reject the hypothesis that P2, ..., Pn are related by nothing but chance.

This is why I said the fact that we can't really hypothesis test on P1 shouldn't matter, intuitively it feels like we can just ignore it and focus on P2, ..., Pn. But I'm not sure.

Anyway, that's basically the thing I'm trying to figure out. It is possible that I have either misdescribed this scenario slightly, or that there are other relevant details that I have failed to consider. That's why I'm hoping for a resource or general starting point for solving problems like this, because the exact nature of the problem may evolve over time. If you've got any thoughts, let me know!

[fifteenleads]

Scientific Method: a process that uses evidence and testing to investigate the unknown, usually following a set of steps in order to arrive at a conclusion.

(Way too tedious. And boring. And so unlike Dazai.)

— An SKK Gakuen AU.

Step One: Make observations.

Most treat it like a "Step Zero", though, to their teacher's dismay. An era of results and instant gratification guarantees zero patience for things that take time.

Chuuya's guilty as charged, of course.

In any case, Dazai is being annoying, as usual.

"Stop blowing raspberries into my ear," he hisses, ducking under his textbook. "It's disgusting as hell."

"Did not," Dazai singsongs in English to the tune of his annoying ringtone. How he manages to even carry a tune despite the bubblegum idol pop blasting from his huge headphones is a mystery, indeed.

Chuuya rolls his eyes at that. "Did, too." He lightly kicks Dazai's leg to get his attention. "Seriously, listen to me. This is important."

Dazai seems to have read his lips, pausing his iPod and taking his headphones off with an annoyed sigh. "What, chibi?"

Ugh, that's definitely intentional.

Chuuya lets that insult slide for now. "I need the budget for the props ASAP," he huffs, arms crossed. "The school festival is already next week, you know."

Five days, to be precise, but Dazai still acts like they still have five weeks. "Ask Higuchi to do it," he drawls, lazily waving Chuuya away. "We still have 120 hours, don't we?"

Dazai turns to him, raising an eye expectantly. Damn him and his lack of sense of urgency sometimes.

That said, though, he always manages to get shit done in time. Every single time, without fail. And Chuuya, in turn, is always baffled at how he does it, every single time.

Today he finds himself asking the same thing all over again. Ugh.

Dazai's still waiting for an answer.

Chuuya's way too tired for this. "120 and counting down," he answers in kind to prove his point. "I need to submit it by today, in case you forgot."

"Higuchi will do it," Dazai simply repeats, wearing his headphones again. "Come back here when you're done. I'll wait for you."

Chuuya opens his mouth, then closes it again. Inhale, exhale. Better.

"Fine," he relents for now, arranging his things. "You'd better still be awake, or I'll dropkick your bony ass to tomorrow. Got it?"

He only gets the same lazy wave in response as he leaves.

When Chuuya comes back to the classroom an hour later, Dazai is fast asleep at his desk, headphones awkwardly displaced around his face.

To be fair, Dazai never said yes at all.

Chuuya could only scratch his head at that. This is one mystery he doesn't feel like solving at all.

.

Step Two: Ask a question.

Easier said than done, really.

They've been seatmates for more than a year and co-class reps for half that time, but that's about it.

Chuuya had cursed his luck to high heaven and back, and Dazai knew it. Reveled in it, even.

Then he got used to it.

He prides himself in being a good team player for the most part, if nothing else. That said, though, this is the first major event they are handling together, and the weight of the responsibility isn't lost on him.

"—Oiiii. Earth to Chuuya?"

Dazai is staring holes into him, pointed nose a mere fingerbreadth from his. He quickly backs away in surprise, sending the stack of paperwork flying to the ground.

Dazai seemed to have expected this somehow, and he sinks back into his seat while breaking into an amused chuckle.

Chuuya slowly puts up a hand to his face, surely an embarrassing flush of red by now. This is what he gets for getting caught off-guard.

The meeting continues where it left off, with Dazai rattling off a string of numbers while Higuchi notes down everything. Luckily, no one else said anything anymore.

Chuuya's still in his own headspace as he walks home alone, having managed to successfully ditch Dazai for once. He stops at a vending machine for a can of iced coffee, since he'll be pulling another all-nighter.

He gets the hazelnut-flavored one by mistake. A reflex, really.

Downing it in one go, Chuuya grimaces at the nutty aftertaste at the back of his throat. He still doesn't see what Dazai likes about it.

That being said.

Since when has he been this preoccupied with thoughts of Dazai?

"Ever since," a voice from the back of his head whispers.

Chuuya feels his face heat up again at the thought. Traitor.

Maybe he's still only flustered about earlier. He also hasn't slept enough the past days. Also stress from festival prep.

Or, he's only confused. Yup, that's definitely it.

That instantly makes him feel better.

.

Step Three: Formulate a hypothesis.

1. Dazai's annoying.    2. Dazai's very annoying.    3. Dazai's very, very annoying.

This one goes into the wastebasket, of course— as if he didn't already know that.

Chuuya's eyes trail to Dazai as he reads aloud a paragraph from the textbook.

It gets increasingly difficult to follow along with the lesson at hand when he's absolutely distracted by that rich, warm voice, carefully enunciating each word in the passage.

"Thank you, Dazai-kun," the teacher nods in satisfaction. "You may sit down."

As Dazai takes his seat, he turns his gaze ever so slightly in Chuuya's direction and their eyes briefly meet.

No sparks fly in all directions, but Chuuya feels a faint jolt of electricity run from his chest outward to every inch of his body.

Then Dazai smirks— the bastard.

1. He's definitely riling me up.

Dazai's smug face lasts only for a fraction of a second before it reverts back to one of disinterest.

Chuuya definitely knows better, though: from the dip of his eyebrows to the twitching of the corner of his lip.

2. He can be serious as hell.

Chuuya ends up mulling over his list through last period. He doesn't notice that class is over until Dazai sneaks up on him and quickly blows into his ear.

"Argh— goddamnit Dazai, every single time!"

Dazai sticks out his tongue in response. "That's for ditching me yesterday."

Chuuya groans in disbelief. Petty much?

He will never understand what he even sees in Dazai at all, at this rate.

Surprisingly, the very thought does the trick for him, and he takes note of it in his notebook at once.

"What's that?" Dazai attempts to peek over his shoulder, but Chuuya manages to evade him, snapping the notebook shut and glaring at him. "None of your business."

It only makes Dazai laugh. "Fine, then. I'll find out by next week."

"Is Nakahara here?" Kunikida from the next class calls from outside. Oh yeah, meeting.

"Gotta go," he excuses himself, half-relieved.

And that was that— for now.

Chuuya doesn't look at the third item on his new list until he's home. It's... strange and vague and unlikely as hell, but there it is anyway, in bold, red ink:

3. This might be a crush (???)

.

Step Three-point-five: Refine the hypothesis.

This is absurd, Chuuya thinks.

He's taken to scribbling his thoughts on a dog-eared spare notebook, since Googling "Do I have a crush on my classmate" was evidently useless.

The result ended up looking like a conspiracy map. Ugh.

Chuuya considers his three-and-a-half pages of chicken scratch before tearing them off.

It feels like he's dug himself into a hole at this point. Not that he minds staying in it, if it means he doesn't have to see Dazai tomorrow.

School festival's tomorrow, though.

Double ugh.

Chuuya honestly thought he was already too old for this shit. No, really.

Now his 15-year-old palpitating... red organ thing is laughing at him for it.

(He still chugs the rest of his coffee anyway. Mmm.)

Running won't solve anything, Nakahara.

Inhale, exhale.

Back to work:

H0 (null): He doesn't have a crush on Dazai. H1 (alternative): He has a crush on Dazai.

There, much more... straightforward.

Dazai would probably laugh at him for misusing a stat concept like this, but it serves his purpose just fine. It's not like he'll find out anyway.

It's one or the other.

(He'd have to decide sooner or later, anyway. Best to strike while the iron is hot.)

.

Step Four: Gather data.

(Because there's no time to experiment.)

It's only Day One, but micromanaging proves to be more challenging than expected. It comes with being second-in-command though, so Chuuya takes it all in stride.

Dazai, on the other hand, is on his phone, mindlessly scrolling and tapping and humming to himself between listening to the team's reports and ordering everyone else around.

Magnificent bastard's a born leader.

Chuuya peeks at his own phone; stopwatch app's still running

Dazai's been on his mind for... 6 hours now.

(No, really. Despite all the chaos. Yes, he's been keeping track.)

Others:

1. They've been using the same shampoo. The smell of activated charcoal has never been this alluring.    2. They think in the same way, apparently. Higuchi of all people had noticed. "You realized just now?"

And... And!...

3. They've been sharing breakfast for a year now. Bites out of the same bread, gulps from the same bottle of water, the works.

It makes Chuuya run for the nearest faucet to scrub off the blush on his face.

He's only left with cat-scratch nail marks and a soaking wet shirt for it, so clearly he shouldn't have bothered.

Welcome to adolescence.

Dazai is mildly amused when Chuuya returns to the classroom. "Had fun, chibi?"

No thanks to you, stupid beanpole.

Day Two isn't any different, but they're more used to the work by then, so they manage to close up much earlier.

Chuuya and Dazai are the last to leave the classroom, having finished the stocks inventory for Day 3 while everyone else went to enjoy the festival.

It's five PM.

"Ah, freedom!" Dazai yawns loudly as he says this, stretching his arms upward before swinging them around.

Chuuya ducks to the side to avoid getting hit. "Ugh, watch it!"

To his credit, Dazai drops his arms back at once. "Oh. Sorry."

He adds a smile to that. It's beautiful.

How hadn't he noticed that before?

The early sunset bathes the corridor in pale red-orange, as well as their white polo shirts. Dazai's messy hair seems to shine, too, if anything.

Chuuya's reaching up to touch it before he realizes. Greasy but soft.

Also: "You have freckles."

Dazai's confused at the sudden contact. He doesn't withdraw, though. "You, too." A smile. "Faint ones, as small as you are, across your nose."

Then he leans in and traces the cat-scratch marks on Chuuya's cheeks. "You've been distracted since last week. What happened?"

.

Step Five: Analyze the data.

Step Six: Draw a conclusion.

Step Seven: Share your findings.

...

Wait, wait, wait.

The moment feels like a jolt of electricity and the numbness after, and then some. Those who said people short-circuit were onto something, after all.

Chuuya doesn't register anything for the entire minute Dazai shakes him back to reality.

Then something wet goes into his ear.

He lets out an unholy screech right there and then, instinctively covering his ear in disgust. Dazai, too, has a finger in both of his, face contorted into something between a wince and a grin.

A beat.

Two more.

And Chuuya laughs his head off. He doesn't know anymore.

Dazai does, too, and they devolve into a pair of crazy hyenas— not that anyone would notice.

It's only a good five minutes later that they catch their breath, slumped on the wall, leaning into each other for support.

"You okay now?" Dazai asks him, still trying not to laugh.

Chuuya only huffs loudly in reply. Dazai takes it as a yes.

"Now that that's out of our system,"— and he goes back to business mode— "will you tell me what's going on?"

Hypothesis 2: Dazai can be serious at times.

(He has always been, though.

Chuuya only refused to see it.)

The next thing he knows, their faces are too close for comfort.

Chuuya takes a nervous gulp. It felt more like gasping for air, the way Dazai frowns at him for it.

Hypothesis 1: Dazai likes to rile him up.

(Maybe? Why, though?

Now he's not so sure anymore.)

Maybe it would be wiser to just forget it. This only happened because he overthought many things.

There's still time to back out.

Dazai won't let him, though, if the intense glare he has on now is any indication.

Inhale, exhale.

Moment of truth:

"Here's the deal" Chuuya starts, momentarily avoiding Dazai's gaze as he finds the right words to say. "We've worked together for so long now. And yes, I still think you're annoying as hell."

Dazai merely hums at that, as if he were expecting it. He doesn't say anything, though.

"A lot of times, though, you pull through. Get things done— magnificently at that. I really don't know how you do it, sometimes.

"The past week made me think about these things. Maybe even earlier than that. Who knows? Does it even matter?

"In any case, I realized something."

By now, the sunset is as deep red as his cheeks, and he feels himself burning up inside.

(Running now won't solve anything.

One or the other.)

Chuuya meets Dazai's eyes.

It's now or never.

"I like you," he says with finality. "And that's all you're getting out of me for now."

Chuuya lets out another huff to prove his point, and holds his breath. And waits.

A beat.

Two more.

It's Dazai who sighs in relief.

And what a sight to behold: his lithe form slumping forward against Chuuya's, the tension in his muscles dissipating with the remnants of the afternoon heat.

"Whew," Dazai finally manages after a while, "you finally said it."

"... Huh?"

"I told you, right? I'll find out soon."

"You didn't read my notes."

"Of course not," Dazai laughs. "You /were/ mumbling a little too loud to yourself these days, though. It was easy to piece things together."

Ugh.

Chuuya rubs at his temples. If only he has something to chuck into Dazai's face right now.

It doesn't explain Dazai's exaggerated reaction just now, though...which he isn't at all trying to cover up, unlike all the times he played pranks before. Unless..

...Oh.

It takes Chuuya only a moment: "You—"

"Yeah," Dazai breathes out. "And that's all you're getting from me, too."

No problems there. Chuuya likes straightforward people.

He still headbutts Dazai for it, though. "Payback," he says simply before he hears complaints.

"Fair enough," Dazai mutters under his breath. "We even now?"

"Yeah."

A bit anticlimactic, all things considered, but Chuuya finds he likes it, too.

Now that that's out of his system, though... "Now what?"

It's a pretty loaded question, and they both know it. No one just suddenly admits and enters into... whatever this is, without a plan.

Dazai stares back, just as cluelessly— but not for long: "I think I know what."

Chuuya decides he still doesn't like that grin at all.

"Remember the lab primer in science? There's a certain procedure we follow to investigate what we don't know."

This time, it's Chuuya who slumps. Good lord.

.

Step Eight: Start over.

.

.

.

For Kiro.

[adj444]

JAN. 23 '23

AG. SCIENCE: milk production & manufacturing & testing & technologies & auuuugghhhhhhggghhhhh

MATHS: ok we're on our final chapter we R doing stats analysis and things like that and we did hypotheses today so the first initial claim made about something is H^0 which is the null hypothesis and then H^1 is the alternative hypothesis and its just the opposite of what H^0 claims. questions that we'll get on it will like give us a claim and then make us identify stuff like what the null & alternative hypotheses are, sample size, sample proportion (p̂ = amt of ppl that answered a certain way / sample size), margin of error (1 / sqrt of sample size), confidence interval ([p̂ -E), (p̂ + E)] and then if it confirms or rejects H^0 if it fits into the confidence interval or not (p̂ - E) < p̂ < (p̂ + E)

BUSINESS: ummm OK sooo im realizingg that ive been neglecting business a bit ..... INDUSTRIAL RELATIONS = relationship between employee and employers, good industrial relationships = ↑productivity ↑satisfaction ↑motivation ↓absenteeism ↓turnover rate; industrial relations CONFLICT = pay, working conditions, discrimination, technology, redundancy, unfair dismissal, cost of living (inflation); PAY CLAIM = demand made by employees to their employer for an increase in pay- cost of living claim, comparability claim (someone else in the same sector/job makes more), productivity claim (doing more than originally contracted) TRADE UNION = INTEREST GROUP of workers in a sector advocating for fair working conditions, SHOP STEWARD elected by trade union members in a workplace to act as the unions rep in that workplace, provides feedback to union + gives advice and support to workers about industrial conflict + resolves disputes = employees rights protected, given info and support, better pay, working conds, awareness, faster negotiation, change, health n safety; LEGAL INDUSTRIAL ACTIONS = token stoppage (stopping working for a short period of time in the workday), official strike (voted on by employees, given a 1-week notice to employer), all-out (all employees, not just the ones involved); ILLEGAL INDUSTRIAL ACTIONS = unofficial strike (no vote or notice), wildcat/lightnig strike, political strike (striking for political causes during own work hours); STAKEHOLDERS AFFECTED BY IND. ACTION = consumers (not able 2 use service, go somewhere else, unsatisfactory experience), suppliers (dont have you to buy their goods, can result in spoilage or surplus), shareholders (share price down cuz profits, public image negatively effected), competitors (benefit from customers choosing their available service over their typical now-unavailable service); BARGAINING = mgmt and employees meet to discuss issues (individual, collective, national collective / social partnership); NON-LEG METHODS OF SOLVING = meeting and talking → negotiation → conciliation (3rd party listens to individuals, tries to get them 2 come 2 an agreement) → mediation (3rd party tries to get an agreement between 2 ppl by messenging between the two, outlinining resolution) → arbitration (you agree to accept the solution before you know what it is)

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Understanding The World Via Math

Unfortunately, most individuals don't search for bias or errors, so they don't appear to be noticed. Thus, individuals may typically consider that something is true even if it isn't properly represented. To make knowledge gathered from statistics plausible and correct, the sample taken have to be consultant of the entire.

visit to know more about :data scientist course in hyderabad In distinction, an observational study does not involve experimental manipulation. In apply, while many elements of knowledge science depend on calculus, you might not must learn as much as you might count on. For most data scientists, it’s solely really necessary to grasp the principles of calculus, and the way these principles would possibly have an result on your models. When you Google for the maths necessities for information science, the three matters that consistently come up are calculus, linear algebra, and statistics. The excellent news is that — for most knowledge science positions — the one kind of math you have to turn out to be intimately conversant in is statistics. Twelfth-grade students performing at the NAEP Proficient degree ought to constantly integrate mathematical ideas and procedures to the answer of extra complicated problems in the five NAEP content areas. It is largely equivalent to the SAT exam, however is split into 4 areas, rather than two. The ACT exam incorporates sections on English, reading comprehension, arithmetic, and science. We are significantly thinking about student scores on the mathematics and science components of the exam, because the tested abilities and information appear associated to those most utilized in  introductory statistics. Exploratory data analysis is an approach to analyzing data sets to summarize their main traits, often with visible strategies. A statistical model can be utilized or not, but primarily EDA is for seeing what the info can inform us past the formal modeling or speculation testing task. The commonplace approach is to check a null hypothesis against another hypothesis. A important region is the set of values of the estimator that results in refuting the null hypothesis. The statistical energy of a take a look at is the likelihood that it correctly rejects the null speculation when the null hypothesis is false. The second wave of the 1910s and 20s was initiated by William Sealy Gosset, and reached its culmination within the insights of Ronald Fisher, who wrote the textbooks that had been to define the educational discipline in universities around the world. The course is designed primarily for enterprise majors; however students of different majors additionally enroll within the course, most notably journalism majors. There is a arithmetic prerequisite of precalculus-level abilities demonstrated by both finishing precalculus with a grade of C or better, or putting sufficiently extremely on the college's math placement examination taken by getting into freshmen. Twelfth-grade students performing at the NAEP Advanced stage ought to perceive the operate idea, and be able to examine and apply the numeric, algebraic, and graphical properties of capabilities. They should apply their knowledge of  algebra, geometry, and statistics to resolve issues in additional advanced areas of continuous and discrete arithmetic. Any international contexts used in math ought to add to an understanding of the mathematics, in addition to the world. To try this, lecturers should keep focused on  educating good, sound, rigorous and appropriate math content and use global examples that work. For instance, learners will discover little relevance in solving a word downside in Europe using kilometers as an alternative of miles when devices already convert the numbers easily. Deadlines and last-minute requests for knowledge or evaluation may require overtime. Students majoring in statistics additionally might take courses in another subject, similar to pc science, life sciences, or bodily sciences. These programs might assist put together students to work in quite a lot of industries. The earlier younger learners can put these abilities to practice, the extra probably we will remain an innovation society and economy. Additional training wanted to realize competency within the skills wanted on this occupation. The Job Outlook tab describes the components that affect employment progress or decline within the occupation, and in some situations, describes the connection between the variety of job seekers and the variety of job openings. The State and Area Data tab supplies hyperlinks to state and space occupational information from the Occupational Employment and Wage Statistics program, state projections data from Projections Central, and occupational info from the Department of Labor's CareerOneStop. Market Research Analysts Market analysis analysts examine consumer preferences, enterprise conditions, and other elements to assess potential sales of a services or products. They also may go on teams with engineers, scientists, and other specialists. We additionally examine for multicollinearity between the varied math and academic variables and between the maths variables and race and gender. We discover little proof that multicollinearity is an issue analyzing correlation coefficients. In addition, we evaluate regressions, dropping one of many math variables and then looking at the impact on the t-statistics of the remaining variables; we discover no significant modifications. The abstract statistics for the dependent variable, “Grade in Course” are also reported in Table 1. At this college, course grades are given out as four.zero, which is equivalent to an A, 3.5, which is equivalent to a B+, 3.0 which is equal to a B, and so forth. Students most commonly earned a B, though over 10% of students earned a grade decrease than a C. Although these are produced from the same calculations as these of hypothesis checks or p-values, they describe both the size of the impact and the uncertainty surrounding it. Statistics rarely give a simple Yes/No type answer to the question beneath evaluation. Interpretation typically comes down to the extent of statistical significance utilized to the numbers and infrequently refers to the likelihood of a price precisely rejecting the null hypothesis (sometimes known as the p-value). A random variable that may be a perform of the random pattern and of the unknown parameter, however whose chance distribution doesn't depend upon the unknown parameter is called a pivotal amount or pivot. The process art of Jackson Pollock relied on artistic experiments whereby underlying distributions in nature were artistically revealed. With the advent of computer systems, statistical strategies have been utilized to formalize such distribution-driven pure processes to make and analyze transferring video artwork. A descriptive statistic is a summary statistic that quantitatively describes or summarizes features of a collection of knowledge, while descriptive statistics within the mass noun sense is the method of utilizing and analyzing those statistics. This meant dropping roughly sixteen college students in each of the three situations examined. The coefficients on Science ACT and math quiz rating rise and become more important. Projected employment of mathematicians and statisticians varies by occupation . Employment development for statisticians is expected to result from more widespread use of statistical analysis to tell business, healthcare, and policy selections. The quantity of digitally stored information will increase over the projections decade as individuals and companies continue to conduct business on-line and use social media, smartphones, and other mobile gadgets. This suggests that the maths quiz rating is basically in keeping with other measures of scholar educational performance, and can be taken as a dependable measure of pupil mathematics ability. The outcomes from the interaction term specification of the model exhibits that some traits or skills are valued extra extremely in some professors' courses than in others. But extra essential are the abilities which are persistently valued across the three professors to approximately the identical degree - science skills, as measured by the science portion of the ACT exam, and the math skills assessed by our primary arithmetic quiz. If sure abilities are persistently useful for students, regardless of the course format or instructing fashion of the professor, then we must be paying more consideration to growing these skills prior to or concurrently with students taking the course. Define, differentiate, and combine features represented as energy sequence expansions, including Taylor collection, and clear up related problems. Model and clear up bodily phenomena utilizing integration/differential equations. If you're considering graduate faculty in mathematics, you must think about participating in some research as  an undergraduate. There are alternatives to do so with professors in our department or at other establishments through the summer season at an REU .

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Data Science in Hyderabad

The entry they supply is very helpful to pay attention the courses repeatedly. Yes, anybody can attend a free demo class and you may attend the primary 3 sessions of the training program free of charge. We present a first of its sort profit for all of the members, where they will once more attend the coaching sessions free of charge in the event that they couldn’t complete their previous coaching program for various reasons. Hyderabad is emerging as a hub for software program growth and providing abundant alternatives. Data Science is among the trending courses of this period, which has plenty of scopes. It presents multiple alternatives for aspirants who want to excel successfully in their careers.

Begin by working through tutorials or Udemy courses on the subject of your selection. Once you could have developed a base in the skills that curiosity you, it could possibly assist to speak with somebody in the subject. Find out what abilities employers are looking for and continue to learn these skills. When learning on your own, setting practical learning targets can hold you motivated. I learnt statistics , machine studying , python , numpy , scikit-study , SQL. I actually have taken online training and comfortably learnt from my house. They have also offered assignments and cleared all my doubts.

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Learn about dealing with multiple classes in output variables including nominal in addition to ordinal knowledge. Understand how to carry out testing of those assumptions to make decisions for business problems. Learn about various kinds of Hypothesis testing and its statistics. You will learn the different circumstances of the Hypothesis table, specifically Null Hypothesis, Alternative hypothesis, Type I error and Type II error. The conditions for conducting a Hypothesis check, interpretation of the outcomes shall be mentioned on this module. In this tutorial you will learn intimately about steady chance distribution.

In addition to the mid-semester and comprehensive examinations, scholar will need to also participate in an online quiz or do an project and submit it on-line as per the course plan. The learners' performance is assessed constantly throughout the semester utilizing varied tools such as quiz, assignments, mid-semester and complete exams. The evaluation results are shared with the learners to enhance their efficiency. Each course will entail a minimal of 1 Assignment/ Quiz, a Mid-semester exam and a last Comprehensive examination.

Through dedicated mentoring classes, you’ll learn to solve an actual-world, industry-aligned data science drawback, from knowledge processing and model constructing to reporting your business results and insights. The project is the ultimate step in the Data Scientist Master's Program and will allow you to to point out your expertise in data science to employers. This Tableau certification course helps you grasp Tableau Desktop, a world-extensive utilized knowledge visualization, reporting, and enterprise intelligence device.

Just don’t overlook to make full use of our school’s priceless assist. In addition, a number of trade bodies similar to Analytics India Magazine, KDnuggets, CIO.com acknowledged and awarded INSOFE’s Data Science Program, since 2011. More than 500+ Companies yr-on-year recruit INSOFE college students as Data Scientists. This popularity amongst Academia and Industry is one of the distinctive strengths of INSOFE.

Assignments given helped to have very good handson on machine studying strategies. Syllabus covered, class classes and assignments accompanied by private analysis and homework on methods taught definitely helps. The prime focus of this Data Science Training in Hyderabad is to rework the students into changing into dominant Data Science professionals. There are a number of reasons why there’s an exclusive rise in the demand for Data Scientists everywhere in the world. Most of the enterprises these days are relying on knowledge analytical models in Data Science to amass & retain their prospects. By harnessing the ability of Big Data, Data Scientists might help enterprises higher understanding their customer preferences, predict the trends, and also analyzes the underlying business dangers and threats.

However, should you already know another programming language, you'll probably be able to decide up Python very quickly. Imagine how you would really feel when you have the skills to investigate complicated enterprise information, thereby empowering you to make correct gross sales predictions or determine promising development opportunities on your group. The data you purchase from these actual enterprise case studies will help you construct the inspiration for the final Capstone Project, which is designed to be the watershed second of your Data Science profession. KPMG in India is the Knowledge Partner for the Data Science Prodegree course.

This course courses all popular ML algorithms as detailed in syllabus tab. Pre-course research lets you develop your data on the basics of Data Science and Machine Learning. It is a self-study section that needs to be completed before getting into to section 2 module. Furthermore, it facilitates the candidates to follow scripts at a cloud lab conveniently. Data Science in Hyderabad is turning into the most coveted subject. The coach was superb and helped me clear all my doubts on the subject matter.360digitmg is among the best Data Science Institutes in Hyderabad. I stored searching many institutes, and then I discovered 360digitmg, I approached and attended knowledge science coaching demo, and then I realized that this is among the best coaching institutes that I ought to select. That's the place I started studying Data Science coaching on the Hitech city branch of Hyderabad. I should say that I'm very much glad about the trainers and curriculum. I recommend anybody who needs to pursue their career as a Data Science expert then now.Simplilearn is a gateway for people who wish to enter into the fields of Data Science, AI or Cloud. I found that is to be probably the greatest online teacher-led portals, and I would undoubtedly recommend it. After the certification, I was in a position to change my job function from a Hadoop Developer to a Big Data Engineer with a great wage hike.Please check with the coordinators about coaching choices in your location. Hyderabad has an ideal talent growth ecosystem to allow beginners to senior professionals to change to Data Science field. Be it a small company or an MNC, they want a Data scientist to handle their giant pool of knowledge. In-depth information on Data Mining, Data forecasting, and Data Visualization.

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In all our applications, students enjoy the double advantages of professional providers by INSOFE and the college partner. The project is about translating textual content from one language to another. To obtain the target, students explore encoder-decoder architectures utilizing techniques like LSTMs, Attention fashions, and transformers. The project helps to determine numerous components that influence the gross sales of products and come up with strategies to enhance enterprise based on data exploration and evaluation. A complete introduction to data science in the actual world with sixteen credits price of technology and business education. We provide coaching varied varieties like classroom coaching and online coaching. Offering Enterprise-Wide Insight – Data Science instruments and strategies develops interactive and dynamic visualization instruments that allow enterprise Enterprise to analyze, view, and benefit from the info.Learn about pure language processing strategies similar to Parts-of-Speech tagging, syntactic, and semantic modeling of languages. It is also a rigorous program with five offline lessons of 4 hours every week. This program has been ranked as the #1 program for bringing together one of the best of academic and business excellence, with Purdue and IBM. The Data Science course could be completed in around six months when you dedicate a few hours every day to studying. Any graduate who has successfully completed our Data Science Institutes in Hyderabad is eligible to take part in the JobAssist program. No, the JobAssist program is designed to help you to find your dream job. It will maximize your potential and chances of touchdown a profitable job.Redesigning and updating CVs with the precision of an insider to help you land that coveted job. With our internationally recognized KPMG-endorsed Data Science Institutes in Hyderabad, you're guaranteed to provide your career profile significant advantages. A key cornerstone of our Data Science Prodegree is that this Capstone Project designed to offer invaluable insights that can help you remedy real business issues like a knowledgeable Data Scientist.

360DigiTMG - Data Analytics, Data Science Course Training Hyderabad

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[lanyardwearingteen]

GEE16: The Entrepreneurial Mind BLOG 2

Crossing The Boundaries: Taking First Step 

Couple of days later our group of five was formed, coerce into a single entity in order to traverse the road of entrepreneurial education together. We will known as the Enjinerrs. The name is actually unofficial but I like how it sounds, I need to deliberate with the team with regards to this matter.

On the first couple of days in our team deliberation and planning, the team decided to tackle problems concerning the environment and the individual health as we deemed it as a priority in helping the environment and the community grow as a whole.

Specifically we tackled three (3) problems:

1. Excess biodegradable waste of the coconut plantations in the Philippines;

2. Unsanitary drinking water in some of the rural and urban areas in the Philippines; and

3.Existence of recyclables solid pollutants that was not utilize.

For our startup to fly, rather for our project to be successful we devise three critically planned methods that is not based on assumptions, but rather based on data mining and research referencing and also taking economic growth into consideration preferably Entrepreneurship into consideration, we have devised the following:

1. Convert the excess biodegradable waste into activated carbon;

2. Utilize the activated carbon with the fabricated recycled scraps into a water filtering device; and

3. Fabricate and design a water filter using recyclable and sanitize scraps.

Although, the project sounds common and shallow in order to cope up with the current trend in the market. What this actually possessed is something that the market doesn’t have since we’ll incorporate engineering directives and technological advancement with the device that we want to manifest.

Back in High School the second project that my team have developed is quite similar, it is a smart tap water quality monitoring device integrated with a microcontroller that works on real time. It runs on a similar concept the only that is missing is the filtration mechanism but all in all in its own totality it’s a good efficient and an accurate device that is proven and tested through various test.

So I’m quite excited for our team’s proposal for this project.

Anyway back at the main topic at hand, before the team decided to pursue this startup we have devise a hypothesis in order to guarantee a result. So have formulated four hypothesis, two (2) alternative hypothesis and also two (2) null hypothesis.

HA1: There’s a necessity to apply a water monitoring and a filtration device to ensure the safety and cleanliness of drinking water.

HA2: The presence of biodegradable coconut waste on coconut plantations exhibits the necessity for a direct solution.

H01: There’s no need to apply a water monitoring and a filtration device to ensure the safety and cleanliness of drinking water.

H02: The presence of biodegradable coconut waste on coconut plantations doesn’t exhibits the necessity for a direct solution.

So, questions now would be, How did we proceed with this project knowing we have so many hypothesis? The answer for that question would be we just proceeded, the hypothesis that we formulated aren’t even that much. Given with time effort and of course experience, it’s easily solved.

In order to test the hypothesis the team have followed two mechanism; a) using survey questionnaires (rather online interview through messenger since it’s the most convenient way of action in the midst of this global pandemic) second through literature referencing for validation of the themes that existed on the respondents answer.

Our questionnaire rather interview have two (2) parts, with Part A. relating to open ended question about water resources and Part B. relating to questions focus on biodegradable and is composed of six (6) questions. The question are actually qualitatively open-ended in order to gather qualitative results. In order to determine its coherence when it comes to testing the hypothesis.

(Interview questions)

Part A.

1. Necessity of safe water

2. Necessity of clean drinking water

3. Necessity of monitoring water quality.

4. Necessity of clean access to drinking water in a community.

Part B.

1. Problems with biodegradable waste? ex. residues of biodegradable waste on coconut plantations in the Philippines...

2. Necessity for actions to resolve the existence of the biodegradable waste.

So for this phase in our task, the team have interviewed 10 respondents through messenger and compiled all results to conclude the themes present on their answers. For ethical and data privacy purposes, the team won’t release a documentation on what happened during the conversation. I don’t know about what my co-member will do, but I as a former student-researcher with 6 years of experience on the field won’t do it so casually as I follow a strict ethical conduct on matters like this. However, I may released a censored documentation.

So the common theme formulated by the interviews goes as follows:

1. Safe water is necessary.

2. Clean drinking water is necessary.

3. Monitoring our drinking water is essential as it’s a matter that relates to the health of the individual.

4. A community deserves clean access towards drinking water.

5. Biodegradable waste is a problem depending on isolated cases and minor exception.

6. In order to resolve problems with biodegradable waste proper management is necessary.

So, based on deduce results there’s a necessity to apply a water monitoring and a filtration device to ensure the safety and cleanliness of drinking water and the presence of biodegradable coconut waste on coconut plantations exhibits the necessity for a direct solution. In conclusion, the team accepts all the alternative hypothesis and rejects the null hypothesis. Lastly, this ensures the slight margin of success for the project of the team.

The question on your mind now would, I presume “What are the other option that we have aside from this project? I mean, we could have chosen different projects especially in the current pandemic where the trend and competition in the market with regards to medical equipment is high, if we want to become an entrepreneur then we need to stay with trend. However, there’s problem with that and it is a matter of credibility and credentials necessary for the work. The thing is, we are not biomedical engineers that would develop medical devices and you can’t just trust a company without proper credentials as it is necessary to be coherent with the field. What I am trying to imply is, let the expert handle their works.

As to why we chose this project, according to recent research conducted by the water.org, the team have learn that, out of 109 million people living in the Philippines, nearly seven million rely on unsafe and unsustainable water sources and 24 million lack access to improved sanitation. Despite its growing economy, the Philippines faces significant challenges in terms of water and sanitation access. The country is rapidly urbanizing, and its growing cities struggle to provide new residents with adequate water and sanitation services. And the team have decided that we can’t just ignore the existence of those people.

[didanawisgi]

Selected Psi Research Publications by Dean Radin Ph.D

This is a selected list of peer-reviewed journal articles about psi (psychic) phenomena, most published in the 21st century. There are also some papers of historical interest and other resources. A comprehensive list of important articles and books would run into the thousands. Click on the title of an article to download it.

The Parapsychological Association – an international professional organization for scientists and scholars interested in psi phenomena – is an elected affiliate of the American Association for the Advancement of Science, the largest scientific organization in the world and the publisher of the journal Science, one of the most prominent scientific journals.

I mention this because some individuals who call themselves “parapsychologists” are not scientists. They are better described as paranormal enthusiasts, ghost hunters, exorcists, or other practitioners of occult or esoteric arts. While such activities are interesting to many in the general population, the people engaged in them are not practicing science as defined by the AAAS, and as such their use of the term parapsychologist is inappropriate.

This page is maintained by Dean Radin. Last updated May 3, 2016.

Healing at a Distance

Astin et al (2000). The Efficacy of “Distant Healing”: A Systematic Review of Randomized Trials

Leibovici (2001). Effects of remote, retroactive intercessory prayer on outcomes in patients with bloodstream infection: randomised controlled trial

Krucoff et al (2001).Integrative noetic therapies as adjuncts to percutaneous intervention during unstable coronary syndromes: Monitoring and Actualization of Noetic Training (MANTRA) feasibility pilot

Radin et al (2004). Possible effects of healing intention on cell cultures and truly random events.

Krucoff et al (2005). Music, imagery, touch, and prayer as adjuncts to interventional cardiac care: the Monitoring and Actualisation of Noetic Trainings (MANTRA) II randomised study

Benson et al (2006).  Study of the therapeutic effects of intercessory prayer (STEP) in cardiac bypass patients

Masters & Spielmans (2007). Prayer and health: Review, meta-analysis, and research agenda

Radin et al (2008).  Compassionate intention as a therapeutic intervention by partners of  cancer patients: Effects of distant intention on the patients’ autonomic nervous system.

Schlitz et al (2012). Distant healing of surgical wounds: An exploratory study.

Radin et al (2015). Distant healing intention therapies: An overview of the scientific evidence

Physiological correlations at a distance

Duane & Behrendt (1965). Extrasensory electroencephalographic induction between identical twins.

Grinberg-Zylberbaum et al (1994). The Einstein-Podolsky-Rosen Paradox in the Brain: The transferred potential

Wiseman & Schlitz (1997). Experimenter effects and the remote detection of staring.

Standish et al (2003). Evidence of correlated functional magnetic resonance imaging signals between distant human brains.

Wackermann et al (2003). Correlations between brain electrical activities of two spatially separated human subjects

Schmidt et al (2004). Distant intentionality and the feeling of being stared at: Two meta-analyses

Radin (2004).  Event related EEG correlations between isolated human subjects.

Standish et al (2004). Electroencephalographic evidence of correlated event-related signals between the brains of spatially and sensory isolated human subjects

Richards et al (2005). Replicable functional magnetic resonance imaging evidence of correlated brain signals between physically and sensory isolated subjects.

Achterberg et al (2005). Evidence for correlations between distant intentionality and brain function in recipients: A functional magnetic resonance imaging analysis

Radin (2005). The sense of being stared at: A preliminary meta-analysis.

Radin & Schlitz (2005). Gut feelings, intuition, and emotions: An exploratory study.

Schlitz et al (2006). Of two minds: Skeptic-proponent collaboration within parapsychology.

Moulton & Kosslyn (2008). Using neuroimaging to resolve the psi debate.

Ambach (2008). Correlations between the EEGs of two spatially separated subjects − a replication study.

Hinterberger (2010). Searching for neuronal markers of psi: A summary of three studies measuring electrophysiology in distant participants.

Schmidt (2012). Can we help just by good intentions? A meta-analysis of experiments on distant intention effects

Jensen & Parker (2012). Entangled in the womb? A pilot study on the possible physiological connectedness between identical twins with different embryonic backgrounds.

Parker & Jensen (2013). Further possible physiological connectedness between identical twins: The London study.

Telepathy & ESP

Targ & Puthoff (1974). Information transmission under conditions of sensory shielding.

Puthoff & Targ (1976). A perceptual channel for information transfer over kilometer distance: Historical perspective and recent research

Eisenberg & Donderi (1979). Telepathic transfer of emotional information in humans.

Bem & Honorton (1994). Does psi exist?

Hyman (1994). Anomaly or artifact? Comments on Bem and Honorton

Bem (1994). Response to Hyman

Milton & Wiseman (1999). Does Psi Exist? Lack of Replication of an Anomalous Process of Information Transfer

Sheldrake & Smart (2000). Testing a return-anticipating dog, Kane.

Sheldrake & Smart (2000). A dog that seems to know when his owner to coming home: Videotaped experiments and observations.

Storm & Ertel (2001). Does Psi Exist? Comments on Milton and Wiseman’s (1999) Meta-Analysis of Ganzfeld Research

Milton & Wiseman (2001). Does Psi Exist? Reply to Storm and Ertel (2001)

Sheldrake & Morgana (2003). Testing a language-using parrot for telepathy.

Sheldrake & Smart (2003). Videotaped experiments on telephone telepathy.

Sherwood & Roe (2003). A Review of Dream ESP Studies Conducted Since the Maimonides Dream ESP Programme

Delgado-Romero& Howard (2005). Finding and Correcting Flawed Research Literatures

Hastings (2007). Comment on Delgado-Romero and Howard

Radin (2007). Finding Or Imagining Flawed Research?

Storm et al (2010).  Meta-Analysis of Free-Response Studies, 1992–2008: Assessing the Noise Reduction Model in Parapsychology

Storm et al (2010). A Meta-Analysis With Nothing to Hide: Reply to Hyman (2010)

Tressoldi (2011). Extraordinary claims require extraordinary evidence: the case of non-local perception, a classical and Bayesian review of evidences

Tressoldi et al (2011). Mental Connection at Distance: Useful for Solving Difficult Tasks?

Williams (2011). Revisiting the Ganzfeld ESP Debate: A Basic Review and Assessment

Rouder et al (2013). A Bayes Factor Meta-Analysis of Recent Extrasensory Perception Experiments: Comment on Storm, Tressoldi, and Di Risio (2010)

Storm et al (2013).  Testing the Storm et al. (2010) Meta-Analysis Using Bayesian and Frequentist Approaches: Reply to Rouder et al. (2013)

 General Overviews & Critiques

Utts (1996). An assessment of the evidence for psychic functioning

Alcock (2003). Give the null hypothesis a chance

Parker & Brusewitz (2003). A compendium of the evidence for psi

Carter (2010). Heads I lose, tails you win.

McLuhan (no date). Fraud in psi research.

Survival of Consciousness

van Lommel et al (2001). Near-death experience in survivors of cardiac arrest: a prospective study in the Netherlands

van Lommel (2006). Near-death experience, consciousness, and the brain

Beischel & Schwartz (2007). Anomalous information reception by research mediums demonstrated using a novel triple-blind protocol

Greyson (2010). Seeing dead people not known to have died: “Peak in Darien” experiences

Kelly (2010). Some directions for mediumship research

Kelly & Arcangel (2011). An investigation of mediums who claim to give information about deceased persons

Nahm et al (2011). Terminal lucidity: A review and a case collection.

Facco & Agrillo (2012).   Near-death experiences between science and prejudice

Matlock (2012). Bibliography of reincarnation resources online (articles and books, all downloadable)

Beischel, J., Boccuzzi, M., Biuso, M., & Rock, A. J. (2015). Anomalous information reception by research mediums under blinded conditions II: Replication and extension. EXPLORE: The Journal of Science & Healing, 11(2), 136-142. doi: 10.1016/j.explore.2015.01.001

 Precognition & Presentiment

Honorton & Ferrari (1989). “Future telling”: A meta-analysis of forced-choice precognition experiments, 1935-1987

Spottiswoode & May (2003). Skin Conductance Prestimulus Response: Analyses, Artifacts and a Pilot Study

Radin (2004).  Electrodermal presentiments of future emotions. 

McCraty et al (2004). Electrophysiological Evidence of Intuition: Part 1. The Surprising Role of the Heart

McCraty et al (2004). Electrophysiological Evidence of Intuition: Part 2. A System-Wide Process?

Radin & Lobach (2007). Toward understanding the placebo effect: Investigating a possible retrocausal factor.

Radin & Borges (2009). Intuition through time: What does the seer see?

Bem (2011). Feeling the future: Experimental evidence for anomalous retroactive influences on cognition and affect

Bem et al (2011). Must psychologists change the way they analyze their data?

Bierman (2011). Anomalous switching of the bi-stable percept of a Necker Cube

Radin et al (2011). Electrocortical activity prior to unpredictable stimuli in meditators and non-meditators.

Radin (2011). Predicting the unpredictable: 75 years of experimental evidence

Tressoldi et al (2011). Let your eyes predict : Prediction accuracy of pupillary responses to random alerting and neutral sounds

Galek et al (2012).  Correcting the past: Failures to replicate psi

Mossbridge et al (2012). Predictive physiological anticipation preceding seemingly unpredictable stimuli: a meta-analysis

Bem et al (2015). Feeling the future: A meta-analysis of 90 experiments on the anomalous anticipation of random future events

Theory

Josephson & Pallikari-Viras (1991). Biological utilisation of quantum nonlocality

May et al (1995). Decision augmentation theory: Towards a model of anomalous mental phenomena

Houtkooper (2002). Arguing for an observational theory of paranormal phenomena

Bierman (2003). Does consciousness collapse the wave-packet?

Dunne & Jahn (2005). Consciousness, information, and living systems

Henry (2005). The mental universe

Hiley & Pylkkanen (2005). Can mind affect matter via active information?

Lucadou et al (2007). Synchronistic phenomena as entanglement correlations in generalized quantum theory

Rietdijk (2007). Four-dimensional physics, nonlocal coherence, and paranormal phenomena

Bierman (2010). Consciousness induced restoration of time symmetry (CIRTS ): A psychophysical theoretical perspective

Tressoldi et al (2010). Extrasensory perception and quantum models of cognition.

Tressoldi (2012). Replication unreliability in psychology: elusive phenomena or “elusive” statistical power?

Mind-Matter Interaction

Crookes (1874). Researches in the phenomena of spiritualism

Crookes (1874). Notes of séances with DDH

Medhurst & Goldney (1964). William Crookes and the physical phenomena of mediumship.

Merrifield (1885/1971). Merrifield’s report (on D. D. Home)

Braude (1985). The enigma of Daniel Home.

Zorab (1971).  Were D. D. Home’s ‘spirit hands” ever fraudulently produced?

Jahn (1982). The persistent paradox of psychic phenomena: An engineering perspective.

Inglis (1983). Review of “The spiritualists. The passion for the occult in the nineteenth and twentieth centuries by Ruth Brandon.”

Schmidt (1987). The strange properties of psychokinesis.

Schmidt (1990). Correlation between mental processes and external random events

Radin & Nelson (1989). Evidence for consciousness-related anomalies in random physical systems

Radin & Ferrari (1991). Effects of consciousness on the fall of dice: A meta-analysis

Jahn et al (1997). Correlations of random binary sequences with pre-stated operator intention: A review of a 12-year program.

Nelson et al (2002). Correlations of continuous random data with major world events.

Crawford et al (2003). Alterations in random event measures associated with a healing practice

Freedman et al (2003). Effects of frontal lobe lesions on intentionality and random physical phenomena

Bierman (2004). Does consciousness collapse the wave function?

Jahn & Dunne (2005). The PEAR Proposition.

Bosch et al (2006).  Examining psychokinesis: The interaction of human intention with random number generators

Radin et al (2006). Reexamining psychokinesis.

Radin et al (2006). Assessing the evidence for mind-matter interaction effects.

Radin (2006). Experiments testing models of mind-matter interaction.

Radin. (2008). Testing nonlocal observation as a source of intuitive knowledge.  

Nelson & Bancel (2011). Effects of mass consciousness: Changes in random data during global events.

Radin et al (2012). Consciousness and the double-slit interference pattern: Six experiments

Radin et al (2013). Psychophysical interactions with a double-slit interference pattern

Shiah & Radin (2013). A randomized trial investigating the roles of intention and belief on mood while drinking tea.

Radin et al (2015). Psychophysical interactions with a single-photon double-slit optical system.

Radin et al (2016). Psychophysical modulation of fringe visibility in a distant double-slit optical system.

 Potential Applications

Carpenter (2011). Laboratory psi effects may be put to practical use: Two pilot studies

Schwartz (1980/2000).   Location and reconstruction of a Byzantine structure … [by remote viewing]

Beischel, J., Mosher, C. & Boccuzzi, M. (2014-2015). The possible effects on bereavement of assisted after-death communication during readings with psychic mediums: A continuing bonds perspective. Omega: Journal of Death and Dying, 70(2), 169-194. doi: 10.2190/OM.70.2.b

Some recommended books (click to see book details at Amazon.com)

Radin (1997, 2009). The Conscious Universe: The Scientific Truth of Psychic Phenomena

Radin (2006). Entangled Minds: Extrasensory Experiences in a Quantum Reality

Irwin & Watt (2007). An Introduction to Parapsychology

Mayer (2008). Extraordinary Knowing: Science, Skepticism, and the Inexplicable Powers of the Human Mind

Kelly et al (2009). Irreducible Mind: Toward a Psychology for the 21st Century

Tart (2009). The End of Materialism: How Evidence of the Paranormal Is Bringing Science and Spirit Together

Carter (2010). Science and the Near-Death Experience: How Consciousness Survives Death

Van Lommel (2011). Consciousness Beyond Life: The Science of the Near-Death Experience

Sheldrake (1999; new edition 2011) Dogs That Know When Their Owners Are Coming Home

Alexander (2012). Proof of Heaven: A Neurosurgeon’s Journey into the Afterlife

Carpenter (2012). First Sight: ESP and Parapsychology in Everyday Life

Carter (2012). Science and Psychic Phenomena: The Fall of the House of Skeptics

Targ (2012). The Reality of ESP: A Physicist’s Proof of Psychic Abilities

Beischel (2013). Among Mediums: A Scientist’s Quest for Answers

Sheldrake (2003; new edition 2013) The Sense of Being Stared At, And Other Aspects of the Extended Mind

Radin (2013). Supernormal: Science, Yoga, and the Evidence for Extraordinary Psychic Abilities

Dossey (2014). One Mind: How Our Individual Mind Is Part of a Greater Consciousness and Why It Matters

Broderick & Goertzel (2014). Evidence for Psi: Thirteen Empirical Research Reports

May et al (2014). ESP WARS: East and West: An Account of the Military Use of Psychic Espionage As Narrated by the Key Russian and American Players

May and Marwaha (2014). Anomalous Cognition: Remote Viewing Research and Theory

Kelly (2014). Beyond Physicalism: Toward Reconciliation of Science and Spirituality

Cardeña (2015). Parapsychology: A Handbook for the 21st Century.

May & Marwaha (2015). Extrasensory Perception: Support, Skepticism, and Science 

Websites with access to more articles

Daryl Bem: Click here  

Brian Josephson: Click here

Edwin May: Click here   

Stephan Schwartz, Click here

Rupert Sheldrake: Click here

James Spottiswoode: Click here

Charles Tart: Click here    

Russell Targ: Click here  

Patrizio Tressoldi: Click here

Jessica Utts: Click here

Richard Wiseman: Click here

Journal of Scientific Exploration: Click here

Princeton Engineering Anomalies Research (PEAR) Laboratory: Click here or here.

Division of Perceptual Studies, University of Virginia: Click  here

Esalen Center for Theory and Research: Click here

Windbridge Institute: Click here.

Koestler Unit of the University of Edinburgh: Click here.

Videos

Greyson (2008). Consciousness without brain activity: Near Death Experiences (United Nations talk)

Radin (2008), Science and the taboo of psi (Google TechTalk)

Sheldrake (2008) The extended mind (Google Tech Talk)

… more to be added …

[itsrahulpradeepposts]

Why Python is used in data science? How data science courses help in a successful career post COVID pandemic?

Data science has tremendous growth opportunities and is one of the hot careers in the current world. Many businesses are thriving for skilled data scientists. Data science requires many skills to become an expert – One of the important skills is Python programming. Python is a programming language widely used in many fields. It is considered as the king of the coding world.  Data scientists extensively use this language and even beginners find it easy to learn the Python language. To learn this language, there are many Python data science courses that guide and train you in an effective way.

What is Python?

Python is an interpreted and object-oriented programming language. It is an easily understandable language whose syntaxes can be grasped by a beginner quickly. It was found by Guido in 1991. It is supported in operating systems like Linux, Windows, macOS, and a lot more. The Python is developed and managed by the Python software foundation.

The second version of Python was released in 2000. It features list comprehension and reference counting. This version was officially stopped functioning in 2020. Currently, only the Python version 3.5x and later versions are supported.

Why Python is used in data science?

Python is the most preferred programming language by the data scientists as it effectively resolves tasks.  It is one of the top data science tools used in various industries. It is an ideal language to implement algorithms. Python’s scikit-learn is a vital tool that the data scientist find it useful while solving many machine learning tasks. Data science uses Python libraries to solve a task.

Python is very good when it comes to scalability. It gives you flexibility and multiple solutions for different problems. It is faster than Matlab. The main reason why YouTube started working in Python is because of its exceptional scalability.

Features of Python language

Python has a syntax that can be understood easily.

It has a vast library and community support.

We can easily test codes as it has interactive modes.

The errors that arise can be easily understood and cleared quickly.

It is free software, and it can be downloaded online. Even there are free online Python compilers available.

The code can be extended by adding modules. These modules can also be implemented in other languages like C, C++, etc.

 It offers a programmable interface as it is expressive in nature.

We can code Python anywhere.

The access to this language is simple. So we can easily make the program working.

The different types of Python libraries used for data science 

1.Matplotlib

Matplotlib is used for effective data visualization. It is used to develop line graphs, pie charts, histograms efficiently. It has interactive features like zooming and planning the data in graphics format. The analysis and visualization of data are vital for a company. This library helps to complete the work efficiently.

2.NumPy

NumPy is a library that stands for Numerical Python. As the name suggests, it does statistical and mathematical functions that effectively handles a large n-array. This helps in improving the data and execution rate.

3.Scikit-learn

Scikit- learn is a data science tool used for machine learning. It provides many algorithms and functions that help the user through a constant interface. Therefore, it offers active data sets and capable of solving real-time problems more efficiently.

4.Pandas

Pandas is a library that is used for data analysis and manipulation. Even though the data to be manipulated is large, it does the manipulation job easily and quickly. It is an absolute best tool for data wrangling. It has two types of data structures .i.e. series, and data frame. Series takes care of one-dimensional data, and the data frame takes care of two-dimensional data. 

5.Scipy

Scipy is a popular library majorly used in the data science field. It basically does scientific computation. It contains many sub-modules used primarily in science and engineering fields for FFT, signal, image processing, optimization, integration, interpolation, linear algebra, ODE solvers, etc.

Importance of data science

Data scientists are becoming more important for a company in the 21st century. They are becoming a significant factor in public agencies, private companies, trades, products and non-profit organizations. A data scientist plays as a curator, software programmer, computer scientist, etc. They are the central part of managing the collection of digital data. According to our analysis, we have listed below the major reasons why data science is important in developing the world’s economy.

Data science helps to create a relationship between the company and the client. This connection helps to know the customer’s requirements and work accordingly.

Data scientists are the base for the functioning and the growth of any product. Thus they become an important part as they are involved in doing significant tasks .i.e. data analysis and problem-solving.

There is a vast amount of data travelling around the world and if it is used efficiently, it results in the successful growth of the product.

The resulting products have a storytelling capability that creates a reliable connection among the customers. This is one of the reasons why data science is popular.

It can be applied to various industries like health-care, travel, software companies, etc. 

Big data analytics is majorly used to solve the complexities and find a solution for the problems in IT companies, resource management, and human resource.

It greatly influences the retail or local sellers. Currently, due to the emergence of many supermarkets and shops, the customers approaching the retail sellers are drastically decreased. Thus data analytics helps to build a connection between the customers and local sellers.

Are you finding it difficult to answer the questions in an interview? Here are some frequently asked data science interview questions on basic concepts

Q. How to maintain a deployed model?

To maintain a deployed model, we have to

Monitor

Evaluate

Compare

Rebuild

Q. What is random forest model?

Random forest model consists of several decision trees. If you split the data into different sections and assign each group of data a decision tree, the random forest models combine all the trees.

Q. What are recommendation systems?

A recommendation system recommends the products to the users based on their previous purchases or preferences. There are mainly two areas .i.e. collaborative filtering and content-based filtering.

Q. Explain the significance of p-value?

P-value <= 0.5 : rejects the null-hypothesis

P-value > 0.5 : accepts null-hypothesis

P-value = 0.5 : it will either except or deny the null-hypothesis

Q. What is logistic regression?

Logistic regression is a method to obtain a binary result from a linear combination of predictor variables.

Q. What are the steps in building a decision tree?

Take the full data as the input.

Split the dataset in such a way that the separation of the class is maximum.

Split the input.

Follow steps 1 and 2 to the separated data again.

Stop this process after the complete data is separated.

Best Python data science courses

Many websites provide Data Science online courses. Here are the best sites that offer data science training based on Python.

GreatLearning

Coursera

EdX

Alison

Udacity

Skillathon

Konvinity

Simplilearn

How data science courses help in a successful career post-COVID-19 pandemic?  

The economic downfall due to COVID-19 impacts has lead to upskill oneself as the world scenarios are changing drastically. Adding skills to your resume gives an added advantage of getting a job easily. The businesses are going to invest mainly in two domains .i.e. data analysis of customer’s demand and understanding the business numbers. It is nearly impossible to master in data science, but this lockdown may help you become a professional by indulging in data science programs.

Firstly, start searching for the best data science course on the internet. Secondly, make a master plan in such a way that you complete all the courses successfully. Many short-term courses are there online that are similar to the regular courses, but you can complete it within a few days. For example, Analytix Labs are providing these kinds of courses to upskill yourself. So this is the right time where you are free without any work and passing time. You can use this time efficiently by enrolling in these courses and become more skilled in data science than before. These course providers also give a data science certification for the course you did; this will help to build your resume.

Data science is a versatile field that has a broad scope in the current world. These data scientists are the ones who are the pillars of businesses. They use various factors like programming languages, machine learning, and statistics in solving a real-world problem. When it comes to programming languages, it is best to learn Python as it is easy to understand and has an interactive interface. Make efficient use of time in COVID-19 lockdown to upskill and build yourself.

[tenscupcake]

the null hypothesis (4/?)

fitzsimmons. teen. ~4.5k this ch. thank you new readers for your feedback, i appreciate it immensely! i hope you continue to enjoy it. let the pining begin ;) summary: roughly one out of every six people can't feel touch; that is, until their soulmate touches them. fitz and jemma are two indignant contributors to that statistic, content to devote their lives to science rather than searching for their supposed 'other half.' both too clever for high school, they head off to university at sixteen, completely unaware their fates are about to become intertwined. but in a world where soulmates don't always match, it's not always easy to confess to a stranger. a soulmate au with a twist. this chapter on ao3 | back to chapter 1 on ao3

As Fitz desperately searches for an escape route, he finds himself glancing behind him almost compulsively. Whether it’s because he wonders if Jemma will follow him, or or just worried she’ll see him barrelling down the hallway as she goes her own way and think he’s a total madman, he isn’t sure. A bit of both, perhaps. But regardless, she doesn’t appear. Doesn’t exit the lab at all.

Just before he reaches the stairwell that led him to this floor, he comes upon a water closet.

Men’s room: she can’t possibly follow him in here.

He barges inside and, finding it apparently empty, he drops his backpack on the floor and buckles over at the waist, letting out a hopeless groan. His stomach turns as he plays it over in his mind, the high of that fateful touch, the inevitable crash of discovering her empty expression. He wonders whether he should duck into a stall in case he actually does throw up.

Instead, he approaches the nearest sink, confronting his reflection in the above mirror. He’s almost surprised to see the same bloke that he saw in the loo this morning as he brushed his teeth, because he doesn’t feel remotely like the same person.

With heavy, jagged breaths, he holds up his right hand, staring at it in horror.

Needing concrete evidence he hasn’t hallucinated the whole thing, he makes a fist with his left hand. He can tell it’s in a fist – proprioceptors are telling his brain that, and he can see it – but he can’t feel it any more than he could an hour ago.

Taking a deep breath, he makes a fist with his right. Lined with a slick layer of sweat, his fingers slide over textured lines of his palm as they curl against it. Squeezing harder, he feels his skin pulling taut around his knuckles, his fingernails cutting into his palm.

“Oh, God.” The words escape his chest in a dry sob as the reality of what’s happened crashes down on him. He repeats the phrase over and over for lack of a real solution, not caring that he’s sounding more and more insane with each one.

This actually happened.

Well, of course it did. Even standing here, doing nothing, he can feel the bloody stagnant air around his hand.

Pulling back the sleeve on his right arm just a tad, he opens his hand and brings his left index finger up to meet it, lightly dragging it across his palm.

It sends a pleasant, warm shiver through his hand, and by extension, down his spine. He leaps into the air with a gasp, shaking out his hand like he’s been shocked. Pulse racing in his ears, blood rushing into his cheeks.

No one ever said he’d be this sensitive!

“What the hell!”

He continues shaking out his hand, trying to pretend it didn’t feel as good as it did. How creepy is that, getting pleasure from touching your own hand? Bloody hell, though, it felt good. There’s still a distinct, tingly line across his palm where his finger touched.

Feeling too overwhelmed to support his own weight, he grips onto the sides of the sink, only to stumble back again when it’s cold and hard against his right hand like nothing he’s ever experienced.

Stopping once he’s a few feet away, he realizes he’s nearly hyperventilating at this point. If he keeps this up, he’ll be passed out on the questionably clean floor in here in a minute. Resting his arms on top of his head, he tries to control his breathing, at least. To inhale and exhale with some regularity. He splays his fingers and holds his hand out to his side awkwardly so he doesn’t accidentally touch anything else before he’s prepared.

But a short moment later, he hears some shoes skidding on the tile. A tap, tapping sound he can’t quite identify.

Uh oh.

A toilet flushes, and Fitz whirls around to find the large, accessible stall (which he presumed empty) clicking and opening. A college-aged bloke on crutches and a knee-length cast hops through the now-open door, his face screwed up with a suspicious sort of disgust.

“You all right, man?” he asks, eyeing Fitz up and down.

“Yeah,” Fitz rushes out with a nod. His voice cracks in the middle of the word, and it really doesn’t help him make a convincing case that he isn’t too young to possibly belong here. The noise he just made was bloody pubescent.

The bloke hobbles to the adjacent sink to wash his hands, and Fitz does his best to breathe normally and not let his wobbly legs give out while he has an audience.

By the time the bloke finally leaves, Fitz has been sufficiently embarrassed into some semblance of composure.

Composure enough to begin to apply some logic to this mess. To figure out a way to climb out of this massive ditch he’s fallen into.

Okay, first thing’s first: list the givens. Can’t solve even the simplest problem without knowing the givens.

Here’s what he knows:

His limited knowledge of physiology tells him the hands have among the most concentrated nerve endings. He’s probably not a total freak for reacting so strongly, and it likely won’t be as intense everywhere else.

That is assuming he ever acquires touch anywhere else. That would require subsequent contact with Jemma Simmons, which he has no guarantee will happen.

Oh, yeah: Jemma Simmons is his soulmate.

He’s probably not hers.

Despite the fact that he’s got a handful of new active neurons currently going haywire with overstimulation, he thinks it’s actually number four that’s giving him the most trouble.

He thought he was above this, lending any credence to the possibility of a matching soulmate. He thought he didn’t care. Knowing it was all too possible – likely, even, for him – that whoever his soulmate ended up being (if anyone) wouldn’t match up with him, he was making the safe, logical choice by reining himself in. Or so he thought.

But somewhere, deep down, he must have been holding out for a match, after all. He wouldn’t feel so crushed by this outcome if he hadn’t. And right now he hates himself for it.

Suddenly it feels as though the floor’s been pulled out from under him. Head spinning, he covers his face with his normal, still-numb hand, letting out a shaky breath.

Okay. One thing at a time.

He’s not certain that he’s not her soulmate. It’s simply the default position he’s taken. As a scientist, he’s been trained to always assume the null hypothesis to be true unless he has sufficient evidence to reject it. In this case, that means assuming he is not Jemma’s soulmate.

But how does one go about rejecting this sort of null? There are no concrete tests to run, no data to analyse. She didn’t react the way he might expect if he were her soulmate; but to be fair, he didn’t either. And she did seem slightly taken aback, even surprised. There’s a tiny possibility he’s wrong. He desperately wants to cling to that possibility, but is it foolish to have such a hope? Will it only lead to him being exponentially more crushed later on, if he finds out with certainty that he isn’t?

But whether or not he has any hope is irrelevant: he has to find out for certain. He can’t carry on being her lab partner, or seeing her in any context, without getting an answer. If he is her soulmate, they can progress forward with that knowledge. If she isn’t, things could go two ways from there. If she doesn’t have a soulmate at all, things could still work. Maybe. If he doesn’t get too clingy or try to push anything romantic on her. And if she does have one, and it isn’t him, well… that’s when he’ll run the other direction. He’ll have to, for his own wellbeing. But this – being plagued with this ambiguity – is already unbearable, and it’s been mere minutes since he left her presence.

Fitz nearly doubles over again. The more he thinks about this, the more his stomach drops, and his pathetically pierced heart creeps up into his throat.

He didn’t ask for this. He never wanted a soulmate, he’s always said that. He doesn’t have time for one. Time or the desire. He never longed for something he couldn’t understand.

But now he’s had a taste of it, a glorious taste of what it’s like to feel, and he desperately wants more. He wants Jemma to touch him again.

He wants to hold her hand again. He’d like to do it forever, in fact.

He is so screwed.

Overwhelmed, Fitz lets out a hopeless groan that echoes jarringly off the tile walls.

He’s got to talk to someone.

Instinctively, he pulls his phone out of his pocket (with his left hand), and awkwardly mashes out a text to the first person who pops into his head: Mack.

mack.

I met her.

Not wanting to sound mad, he leaves it short. He’ll understand what it means.

But when Mack doesn’t respond straight away, Fitz isn’t sure what to do. He could phone his mum, but she’d probably just pressure him to pursue Jemma. And it’s unlikely she’d understand, anyway, since she hasn’t been through this.

Then again, neither has Mack. But he has to tell someone. He feels fit to burst.

While he’s waiting for Mack to text back, he works on his breathing again. And decides a good distraction to the uncertainty settling like an anchor in his gut will be to experiment with his newly acquired fifth sense.

Hesitantly, he closes the distance between himself and the sink, reaches down slowly with his right hand. The first couple times, the anticipation gets the better of him and he pulls his hand back too soon. But the third time, his fingertips make contact with the ceramic, and he stills his hand for a moment, lingering there. Trying to get used to the flood of signals. Steeling himself as best as he can, he flattens his palm against it, running his hand along the side. All while holding his breath so he doesn’t gasp like a little boy again.

Various physical properties of ceramic run through his mind, and he tries to match them up with the information coming from his hand. Of all the adjectives he can define, there’s only a few he feels confident enough to assign to the sink. Nonetheless, he focuses on newly cataloguing them his head, pairing them with the unique sensations in his hand. For a few moments, at least, it keeps him from spiralling into an anxiety attack over his fate with Jemma. Dense, cool, polished... slippery even, beneath his damp skin.

He clutches at the fabric of his shirt, next, starchy cotton, hard circular plastic buttons. Rubs the fabric of his tie between his thumb and index finger. That’s his favourite so far, aside from Jemma’s hand. Silky. It’s a good one, as far as textures go.

But even doing these simple exercises, his heart is racing again. His hand is getting sweatier by the second. Needing a break from the sheer sensory overload, he lets his arm fall to his side again, still trying to process the last few objects. He resists the urge to wipe his damp hand on his trousers, knowing that would be too much for him to handle.

How do ordinary people cope with this?

He supposes it’ll eventually fade. Desensitisation occurs with auditory and olfactory receptors, and he knows it to be true of mechanoreceptors as well, even if he’s yet to experience it first-hand. He just hopes that happens quickly. He’ll be found out by his peers – or worse, by Jemma – if he’s constantly thrown into a frenzy by every new thing he touches.

Well, he doesn’t have a research proposal for the whole is-he-Jemma’s-soulmate-or-not question, but there is at least a way to avoid outing himself in such a way. He simply has to desensitise his hand a bit. Expose himself to common substances to avoid surprises.

With an objective and a method to achieve it in mind, he suddenly feels a bit less overwhelmed.

Still, if he’s going to confront the world with a brand-new sense, he’s going to need some fresh air. Scooping up his bag from the floor, he hurries out of the claustrophobic loo before he can change his mind.

 -----

 The laboratory door slowly closes itself behind Fitz, but for a while all Jemma is stare numbly at his exit route. She considers going after him, because he’s her bloody soulmate and he can’t have gotten far, but she’s frozen on her feet.

When enough of the shock has warn off to reverse the temporary paralysis, the first thing to move is her newly cursed right hand. Air swishes softly over her skin as she wriggles her fingers. She lifts it up next to her face, staring at it in disbelief. Tentatively, she raises her left hand up to the same level, lightly brushing her thumb over her palm. Just as when Fitz’s hand made contact, the path where her thumb touches explodes with sensation. Delicate friction, the texture of the ridges on the pad of her thumb, the light tug on her skin as she drags along the surface. Thousands of tiny little neurons are triggered in its path, leaving a pleasant electric hum in a distinct line across her palm. A warm, tingling sensation reverberates up her arm, all the way to the back of her neck, making her shiver involuntarily.

With a startled gasp, she pulls her hand out of her thumb’s reach, lightly shaking out her hand to try to stop the foreign fuzzy feelings.

Bloody hell, that felt good. Too good. Why did it feel that good??

And it may as well have someone else touching her – because her thumb didn’t feel any of that. It’s no more responsive than it was five minutes ago.

After giving herself a few moments to recover, and prepare herself for further onslaught, she continues to lightly stroke her right hand with her thumb, mapping out the exact shape of where Fitz’s hand had been. The precise outline of where his larger fingers and thumb had curled around her smaller hand, instantly forging a divide between dysfunctional and newly functional neurons.

It’s only when a classmate at the hood adjacent to theirs asks her if she’s all right that Jemma realizes there are tears streaming down her face.

Without answering their question, she picks up her bag and dashes out of the lab.

She doesn’t stop running until she gets back to her dorm. Exerting effort makes it much harder to think, which is good. She’s certain to drive herself mad as soon as she starts thinking of the repercussions of what just happened.

As soon as she’s within the safety of her own room, she pulls out her phone, only to drop it on the floor when she’s bombarded with the textures of her trousers, the plastic and glass of her phone case. Letting out a groan of frustration, she picks it up with her still-comatose left hand, and texts Daisy to call her as soon as she gets this message. It takes her longer than usual, using only one thumb, but for now, it’s better than being overwhelmed by the bloody screen.

Switching her phone to ‘loud’ and tossing it onto her bed, she slumps against the wall, sinking to the floor and wrapping her arms around her knees. Careful to avoid brushing her hand against anything.

If having her world turned upside down in an instant wasn’t enough to take her breath away, running half a mile certainly is. Now that she has a moment to assess her physiology, it becomes evident that her chest is heaving, her vision getting a bit spotty. She’s hyperventilating. Knowing it’ll do her no good to pass out on the floor of her room, she tries to focus on calming herself down. Rests her head back against the wall and tries to slow her out of control, ragged breaths to a somewhat normal rhythm.

Oh, God, it’s him. It’s him. Of course it had to be him.

As much as she’s always tried to pretend she wasn’t, she’s always been fascinated at the idea of meeting her soulmate. Just too frightened to actually hope she ever would. But somewhere in the back of her mind, she always hoped that if she ever did meet them, they would reveal themselves to her straight away. She’d always had a bad feeling that when (or if) the time ever came, she would be too nervous to do it first.

It turns out, she was right. Her soulmate blundered into her life without a moment’s warning, and as predicted, she completely froze up. Couldn’t find the courage to tell him in the short span of time before he disappeared.  

Uncle Jeff had always told her not to be afraid, to just come out with it, if it ever happened. The man was determined not to let his misfortune affect any of his nieces of nephews.

But how could she not be? Jemma is a scientist. She strives to make decisions not based on her gut, as people tend to do, but based on evidence. And the evidence suggests that mismatching is common enough to warrant caution, if not fear. The memories of her uncle’s encounter merely made that evidence more tangible. Or so she’s convinced herself.

But now she’s in the same position he was, isn’t she? Fitz exhibited none of the typical responses she’d come to anticipate from someone who’s just touched their soulmate for the first time.

But then, neither did she.

It was odd the way he rushed out of there so fast; but he had run into class, so it wasn’t unreasonable he’d also run out. And it seems social interaction isn’t exactly something Fitz excels at.

If there’s one thing Jemma hates, it’s uncertainty. Accepting the hypothesis that she is Fitz’s soulmate, too, would require sufficient evidence that revolves around Fitz himself. The amount of evidence she currently has is unquestionably insufficient, but he is the biggest dependent variable here. She can’t figure out anything for certain without him present. Testing this hypothesis immediately is out of the question, and until she can collect more data, it’s neither safe nor logical to assume she is his soulmate. Scientifically speaking, she has no choice but to assume the opposite: the null hypothesis that she is not.

But Jemma has to admit, it’s difficult for her to remain as objective as she needs to be for scientific investigation when she’s this fraught with emotion. When her heart is begging her to have some hope, whether or not it aligns with scientific reason.

Anger suddenly flashes through her system. She didn’t come to university to meet her bloody soulmate, to have a chance encounter that turned her life upside down whether she wanted it to or not. The entire concept seems predicated on an utter lack of both consent and logic.

But she’s stuck now. It’s happened.

And she can stomp around and be furious all day, convince herself this is merely an untimely interruption in her busy academic schedule. She can spend the next week before she sees him again pretending she doesn’t care whether she’s Fitz’s soulmate, pretending it doesn’t matter.

But she’d be unequivocally lying to herself. Stupid though she knows it to be, a single desire has overtaken her thoughts in the minutes since she left his presence. She wants, desperately, to be the girl Fitz is destined for. She wants to spend every waking moment of the foreseeable future learning everything there is to know about him. She wants him to touch her again. The boy who, merely an hour earlier, she was on the threshold of disliking. Could list of a list of reasons why, in fact.

It just had to be Fitz, didn’t it?

She has a sinking feeling, deep down, that he’s not her match. But a feeling isn’t enough. She needs concrete evidence or she’ll never be able to move on.

The thought of moving on sends a sharp stab of pain through her pathetic heart, and she could just slap herself for it.

Knowing it was such a real possibility to be mismatched, Jemma had done everything she could to prepare herself for such an outcome. More importantly, she never dared to hope that she’d find some mythical happily ever after. Mostly because she didn’t need one. She planned on making a difference in the world, and romantic relationships seemed only to hinder one’s career. At least, such seemed to be the case for women. She was perfectly content – eager, even – to dedicate her life to science rather than men.

But now there are feelings in her chest as unfamiliar as they are absurd – butterflies and yearning and a nagging sense she’s suddenly incomplete. Now she’s fantasising what it’d be like to discover she and Fitz are a match made in the cosmos, after all.

No! she reprimands herself. She can’t go there. Not now. Not yet.

To stop herself from daydreaming about her unwitting soulmate anymore, she busies herself with another pressing matter – the newly functioning synapses in her right hand.

She slowly uncurls herself from the ball she’s in, and carefully lowers her right hand until it’s gently resting on her jeans. Slowly, she curls her fingers, getting a sense of the fabric: its uneven texture, the fact that it wicks away the moisture from her sweaty palm. She reaches her hand down to the rug, next, burying her fingers in it, feeling the thick fibres brush along her fingers but unable to put words to the unique texture in her mind. It’s only a second before she has to pull her hand away, alarmed by the intensity of the sensations.

Before she can stop them, tears are rolling gently down her cheeks again. Silently mourning the fact that she’s spent her whole life missing this vital physiological function. The fact that she’s enduring this sensory overload alone when she’s meant to be sharing it with someone. With Fitz.

Someone taps lightly on her open door, startling Jemma enough that she flinches hard, hitting her elbow against the wall.

Turning toward the door, she sees her RA standing hesitantly in the frame. Jemma throws her left hand over her heart, relieved. Hastily wiping her face with her jumper, she stands up to greet her.

“Hi, May,” she says, sniffling and trying to sober up. “What’s up?” All Jemma can seem to offer is a weak smile.

“I just heard…” May takes in her expression, no doubt seeing red blotches all over her face. “Are you okay?”

May doesn’t exactly look concerned; instead, her features are hard as if she might be angry that Jemma was crying. But Jemma learned early on that May’s solemn looks are deceiving. All the evidence thus far suggests that she cares about Jemma’s wellbeing: she’d been the nicest one here on her first day of orientation. Told her she could come to her with anything, school-related or not.

Before Jemma can answer, her phone blares from where she tossed it on her bed.

“I’m okay,” she lies. “I’m so sorry, I’ve got to get this.” She points to her phone. It’s more important to talk to Daisy first. She can go to May later, if she’s still available.

May simply nods, and leaves her in peace.

Jemma snatches her phone up off her bed with her left hand. Awkward though it is, she’s not ready to freely utilise her right hand yet.

“Daisy?” she answers, surprised by how distraught she sounds.

“Jemma, what’s wrong? Your text sounded urgent.”

“Oh, Daisy, it’s him. I met him.”

“What!? Are you serious?”

“Deadly serious, I’m afraid.”

“What was it like?”

“Would you even understand if I told you?”

Daisy is quiet for a beat. “No. But you still can.”

“I don’t really know how to describe it. It’s like nothing I’ve felt before.”

“How’d it happen?”

“He’s my lab partner in chemistry. We shook hands.”

“Ohhh.” A pause. “Is he cute?”

Jemma thinks about that for a moment, but can’t seem to come up with a definitive answer. She shakes her head, angry with herself for not knowing.

“I dunno.” At first sight, she hadn’t been memorably impressed with his appearance. But when has she ever been upon first meeting someone? It’s so hard to remember his face in clear detail. He was pale, had curly hair, boyish cheeks. But he was wearing goggles for much of the time, and they’d spent much of the two hours staring at their experiment’s progress, rather than each other. Not to mention, right now all she can think about is how sinfully good it felt to touch his hand. “Maybe.”

“Wow. Control your thirst, Jemma.”

She lets out a humourless chuckle.

“Well, what did you both say when you found out?” Daisy prods.

“See, that’s the thing, Dais…” The imminent rejection crashes down on her again, and she swallows down a lump in her throat. “We didn’t.”

“You what?”

“I was too nervous!” she tries to defend herself. “You know I’ve always been scared I’d be mismatched!”

“Yeah, but, Jemma…”

“If he’s not my proper match, it’ll crush me. I wish I could say it wouldn’t but…”

“Okay, it’s okay. We’re gonna figure this out. I’m gonna help you figure this out. Okay?”

She takes in a shaky breath, and nods. “Okay.”

“Why don’t you start at the beginning?”

Jemma does exactly that, telling Daisy about him showing up late, working together, the handshake, the way he ran off before she could say anything (not that she was ready to).

“He ran off?” she asks.

“Sort of, yeah.”

“Think maybe he was just as freaked out as you were by what happened?”

She had considered it, briefly. But hoping for such an event would be foolish.

“Don’t get my hopes up, Daisy.”

“Okay. Sorry.” She lets out a sigh. “You have to find out, though. You can’t go on like this.”

“I know.”

“I’m guessing you won’t just come out and tell him?’’

“Not an option,” Jemma confirms.

“Well, you’re going to have to get it out of him some other way then. You’ll be spending a couple hours with him every week, right? Eventually it’ll come up.”

“Will it?” she asks, not optimistic.

“I’m not really sure what else you could do.”

“You’re right. It’s probably my best option.”

“Please let me know?”

“Of course.”

“And Jemma, even if he isn’t, it’s gonna be okay. You’ll still have me.”

“’Til you meet yours.”

“Don’t even joke about that.”

Jemma genuinely smiles for the first time since she left that lab. “’Kay.”

[murphydbuffalo]

Why do I need such a large sample size for my A/B test?

Running A/B tests is about finding out with some degree of confidence which of two versions of some thing is better. The canonical example would be running a test on the sign up form of your website. At present some percentage of users who see that page sign up or “convert”, and you’d like to see if making some change to the text or look of the page will make a greater percentage of users convert.

You can determine if that’s the case by running a hypothesis test comparing the proportion of users who convert when shown the original version (let’s call this p1) and proportion who convert when shown the new version (let’s call this p2). The null hypothesis is typically something like p1 - p2 = 0, or that there is no real difference between the two versions. And the alternate hypothesis is therefore something like p1 - p2 != 0 or p2 > p1, meaning that there is in fact some difference between the two versions. This difference between the two proportions is called the effect size, and it is often measured in standard deviations. For example if version A shows a conversion rate of 5%, version B shows a rate of 6%, and the standard deviation is 1% then the effect size is 1 standard deviation.

As you probably recall from statistics class back in the day, you must select a significance level for your test. If you see an effect size that is more standard deviations away from the mean than your significance level then you have a “significant” result.

All of this is well and good, but if you’ve looked into recommended sample sizes for running your experiment you’ve likely been surprised by how many examples are required: often many thousands for each version.

What exactly do we gain by using these recommended sample sizes as opposed to running our test until we’ve found a significant result? Quite a lot it turns out. 

The Goal

Looking at your A/B tests only through the lens of significance gives you an incomplete and sometimes misleading picture. I would argue that instead of being concerned with significance, we should be concerned with the likelihood that the conclusions we draw from our test are true, and that those conclusions signify something important to us.

This goal can be broken down into more digestible chunks. First, what does it mean to be concerned with the likelihood of our results being true? This comes down to the fact that there are four possibilities when we run our test:

1. The null hypothesis is false and we reject it. A true positive.

2. The null hypothesis is true and we reject it. A false positive.

3. The null hypothesis is false and we fail to reject it. A false negative.

4. The null hypothesis is true and we fail to reject it. A true negative.

We want to be reasonably confident that our results fall into the true conclusions covered by numbers 1 and 4, and not the false conclusions of numbers 2 and 3.

By adjusting our significance level we can directly control for the likelihood of false positives. A significance level of 5% means that assuming our null hypothesis is true there is a 5% chance that by pure luck we will see a result as or more extreme than that significance level.

That covers false positives, but what about the risk of false negatives? That’s another importance piece of our quest for truth. Power in statistics is the probability of your hypothesis test detecting a positive result when it is present. Said another way it’s the probability of not having a false negative.

So in order to effectively pursue true results we need to be concerned with both the significance level and power.

What about the second part of our goal, conclusions that signify something important to us? This addresses the fact that you can find statistically significant results that are utterly uninteresting and not worth acting on. That is, you could run an A/B test and find a significant result that says “version B is 0.0001% more effective than version A”. Very likely, although it depends on your domain, this difference is meaningless and it wouldn’t be worth the time and effort to run the test and then replace option A with option B.

Crucially, such uninteresting results are more likely to be found as your sample size increases. This is because the larger the sample size the lower the standard deviation of the sampling distribution. Think back to our example from the beginning of the post where we had an effect size of 1% or 1 standard deviation (because our standard deviation was also 1%). If the sample size goes way up, shrinking the standard deviation to 0.1%, then the same results would show an effect size of 10 standard deviations. This would be much, much farther from the mean of the distribution and would almost certainly qualify as a significant result.

The point is that a large enough sample size can make any effect size significant. So it’s important that we define ahead of time the smallest effect size we deem to be meaningful to us. In the context of A/B testing this might mean the smallest effect size that would make it worth our while to wait for our test results and deploy a new version of the feature.

We are going to use the figure we come up with here as something called the Minimum Detectable Effect (MDE) in our sample size calculations. There will be more on MDE towards the end of the post for those who are curious, but it’s not necessary to understand it in detail to grasp what A/B testing sample size calculations should do for you.

What Your Sample Size Tells You

Taken together, what does all of this mean? We want to have a level of confidence that any conclusions we draw are true. We specify that level of confidence in terms of significance level to deal with the probability of false positives and power to deal with the probability of false negatives. We also specify the smallest effect size that is meaningful to us in order to avoid running a test only to find out that we don’t care about its results.

Given all of this we can solve for the smallest sample size that will satisfy all of those parameters. This will tell us “you need X trials per version for your experiment to have this level of significance level and power for an effect size at least as big as your MDE”. If your effect size is bigger than that MDE, awesome! You’ll have an even greater chance of detecting it than your specified level of power.

Somewhat counter-intuitively, you do not want to keep running your test beyond this sample size. Remember, that this means you will increase the risk of detecting as significant results smaller than your MDE, which by your own definition is the smallest effect size you would care to notice.

Equally important is avoiding the opposite temptation: not running your test until you’ve achieved the calculated sample size, and instead stopping the test as soon as you’ve achieved significance. Evan Miller does a wonderful job explaining why you shouldn’t do this, but the short answer is that it biases you towards thinking you have significant results when really you don’t. What if after 500 trials the result is deemed significant, but after 1500 it turns out the result isn’t after all? If you had stopped early you would have drawn the incorrect conclusion about your results.

Whew! That’s a lot and certainly more complicated than simply checking if your result is significant or not. But it is also an approach that will get you results you actually care about with a level of reliability you can be comfortable with.

Postscript - Explaining Minimum Detectable Effect

The MDE is the smallest effect size needed for a test to have at least a certain level of power, given a particular significance level. For example if you know that you want your test to have an significance level of 5% and a power of 80% you could calculate an MDE which would tell you “if I see an effect size equal to or greater than our MDE we will have at least an 80% chance of detecting a positive result given our 5% significance level”.

Jonathan Leirer has a great article explaining this better than I can. But the heart of the concept is that for a positive result the probability distribution of the null hypothesis (the “null distribution”) is not true, rather some alternate hypothesis with its own probability distribution is true. Further, the null distribution and the alternate distribution will be some distance apart, and may have some overlap, thus the possibility of false positives and negatives.

So, if we want a power of 80% the MDE describes how far from our significance level (which is on the null distribution) the alternate distribution mean must be for 80% of the alternate distribution to fit in the space up to that significance level. Said another way, if the alternate hypothesis is true, and 80% of the alternate hypothesis’s probability distribution falls past our significance level, we have an 80% chance of detecting positive results given a significant result. It’s worth remembering here that ”significant” simply means that our observed effect lies beyond our set level of significance level on the probability distribution. A picture really is worth about 1,000,000 words here, so read Jonathan’s article to see a visual of how this works.

[thatsnotcanonpodcasts]

Magnetic Waves, Piracy & Valve

We hope that everyone is well and enjoying the start of the holidays season. This week we have the answer to the mystery of why the Sun is so hot and the dispersal of magnetic waves during solar flares. That’s right, one of those little mysteries that has been confounding scientists for years appears to have been solved with evidence supporting the rejection of the null hypothesis. Ooops, sorry, in other words research that explains why it appears to happen has been developed. So if you would like to know more about why that is then please listen in and enjoy this discussion that does wander off topic occasionally but in a fun way.

Next we look at the effect piracy is having on Marvels profit margin (which as a Disney corporate entity we must acknowledge are very slim margins). We discuss this and consider the alternatives such as going digital like XCT and some of the other projects from our friend Shaun at Comics2movies have begun to do. Buck wanders down memory lane reminiscing about when he was a boy (OK Boomer does not apply here as Buck isn’t that old). Can you believe that comic books used to only cost 15 cents? These days it is $10 and has less of a story in some cases, although XCT is cool if you want a great read.

Last topic is Valve news and what is happening with them. For example did you know that they are in the process of ending their controllers? Also did you know that they have recently had a sale on these controllers? Professor did and has bought one, even though they weren’t on sale here? Also Half-Life Alyx the VR experience game is looking downright awesome, if the promo video is anything to go by this is a game to get into.

As usual we have the regular shout outs, remembrances, birthdays and events for the week. Until next time remember to look out for each other, take care of yourselves and stay hydrated.

Mystery of the magnetic waves - https://www.technology.org/2019/12/02/scientists-crack-60-year-old-mystery-of-suns-magnetic-waves/

Comic Piracy - https://www.bbc.com/news/entertainment-arts-50564713

Valve News

- Steam Controller sale - https://www.theverge.com/good-deals/2019/11/26/20984123/valve-steam-controller-discontinued-sale-price

- Valve Index - https://www.roadtovr.com/valve-index-sold-out-stock-half-life-alyx/

- Half-Life: Alyx announcement - https://www.youtube.com/watch?v=O2W0N3uKXmo

Game currently playing

Buck

– Raid: Shadow Legends - https://raidshadowlegends.com/pc-mac-plarium-play/

Rating – 3.5/5

Professor

– Counterstrike Global Offensive - https://store.steampowered.com/app/730/CounterStrike_Global_Offensive/

Rating – 3/5

DJ

– UNDEFEATED - https://store.steampowered.com/app/1116960/UNDEFEATED/

Rating – 3/5

Other topics discussed

Laser (a device that emits light through a process ofoptical amplification based on the stimulated emission of electromagnetic radiation.)

- https://en.wikipedia.org/wiki/Laser

Corona (Corona Extra is a pale lager produced by Cervecería Modelo in Chicago for domestic distribution and export to all other countries besides the United States, and by Constellation Brands in Canada for export to the United States.)

- https://en.wikipedia.org/wiki/Corona_(beer)

Corona (an aura of plasma that surrounds the Sun and other stars. The Sun's corona extends millions of kilometres into outer space and is most easily seen during a total solar eclipse.)

- https://en.wikipedia.org/wiki/Corona

Solar Eclipse blindness

- https://www.preventblindness.org/solar-eclipse-and-your-eyes

Solar Storm of 1859 (a powerful geomagnetic storm. A solar coronal mass ejection hit Earth's magnetosphere and induced the largest geomagnetic storm on record, September 1–2, 1859.)

- https://en.wikipedia.org/wiki/Solar_storm_of_1859

Earth’s magnetic field (also known as the geomagnetic field, is the magnetic field that extends from the Earth's interior out into space, where it interacts with the solar wind, a stream of charged particles emanating from the Sun.)

- https://en.wikipedia.org/wiki/Earth%27s_magnetic_field

Magnetic Declination in Brisbane

- http://www.magnetic-declination.com/Australia/Brisbane/117433.html

Orienteering (a group of sports that require navigational skills using a map and compass to navigate from point to point in diverse and usually unfamiliar terrain whilst moving at speed.)

- https://en.wikipedia.org/wiki/Orienteering

Comics2movies (Online comic book and memorabilia store that brings independent and rare comics all to one place.)

- https://www.comics2movies.com.au/

Jim Zub’s tweet thread about comic book piracy

- https://twitter.com/JimZub/status/1198939012288974848

Spider-Hulk (Marvel Comics character)

- https://mugen.fandom.com/wiki/Spider-Hulk

How manga takes over comic books

- https://comicbook.com/anime/2019/07/06/anime-executives-manga-taking-over-us-comic-sales-anime-expo/

Price of Absolute Carnage #3 (of 5)

- https://www.comicsetc.com.au/collections/comics/products/absolute-carnage-3-of-4-ac

Price of Watchman graphic novel

- https://www.comicsetc.com.au/collections/paperbacks/products/absolute-watchmen-hc

Online piracy can boost comic sales

- https://torrentfreak.com/online-piracy-can-boost-comic-book-sales-research-finds/

Combined annual domestic box office revenue of superhero movies from 1978 to 2019 (in million U.S. dollars)

- https://www.statista.com/statistics/311931/superhero-movies-box-office-revenue/

Jamie Johnson (Comic book artist)

- https://www.facebook.com/jamiejohnsonillustration/

Stan Lee (American comic book writer, editor, publisher, and producer.)

- https://en.wikipedia.org/wiki/Stan_Lee

Oculus Rift (lineup of virtual reality headsets developed and manufactured by Oculus VR, a division of Facebook Inc., released on March 28, 2016.)

- https://en.wikipedia.org/wiki/Oculus_Rift

Valve Index (virtual reality headset created and manufactured by Valve.)

- https://en.wikipedia.org/wiki/Valve_Index

Star Citizen has now raised over $250m in crowdfunding

- https://www.eurogamer.net/articles/2019-12-02-star-citizen-has-now-raised-over-usd250m-in-crowdfunding

- In Australian Dollars - https://www.kotaku.com.au/2019/12/star-citizen-has-raised-369-million-over-the-last-7-years/

Holden fourth-generation VE Commodore

- https://www.smh.com.au/national/billion-dollar-baby-20060719-gdnzma.html

No Man’s Sky

- https://en.wikipedia.org/wiki/No_Man%27s_Sky

Many A True Nerd playing Fallout 76 BETA

- https://www.youtube.com/watch?v=OWOoADl--6Q

Vantan games (studio behind UNDEFEATED the game)

- https://www.vantan-game.com/index.php

Megatron Downfall (first person superhero game)

- https://store.steampowered.com/app/430210/Megaton_Rainfall/

Arms Race (game mode featured in Counter-Strike: Global Offensive)

- https://counterstrike.fandom.com/wiki/Arms_Race

Peter Lalor (Irish-Australian rebel and, later, politician who rose to fame for his leading role in the Eureka Rebellion, an event controversially identified with the "birth of democracy" in Australia.)

- https://en.wikipedia.org/wiki/Peter_Lalor

Eureka Stockade (1949 movie about the Eureka Stockade)

- https://en.wikipedia.org/wiki/Eureka_Stockade_(1949_film)

15 reasons why India's and Israel's moon-landing attempts both failed during descent.

- https://www.businessinsider.com.au/why-india-israel-failed-moon-landings-failed-final-descent-2019-9?r=US&IR=T

Apocalypse Now (1979 American epicwar film about the Vietnam War, directed, produced and co-written by Francis Ford Coppola.)

- https://en.wikipedia.org/wiki/Apocalypse_Now

DC Fontana (American television script writer and story editor, best known for her work on the original Star Trek franchise and several Western television series.)

- https://en.wikipedia.org/wiki/D._C._Fontana

Greedy Smith (Australian vocalist, keyboardist, harmonicist and songwriter with Australian pop/new wave band Mental As Anything.)

- https://en.wikipedia.org/wiki/Greedy_Smith

Shoutouts

3 Dec 1854 – Battle of the Eureka Stockade: More than 20 gold miners at Ballarat, Victoria, are killed by state troopers in an uprising over mining licences. - https://en.wikipedia.org/wiki/Eureka_Rebellion#Battle_of_the_Eureka_Stockade

3 Dec 1994 – PlayStation was launched - https://www.news.com.au/technology/home-entertainment/gaming/playstation/playstation-25th-anniversary-sony-celebrates-ahead-of-ps5-release/news-story/5479caa4644ced48119c003929f9cfd6

3 Dec 2014 – The Japanese space agency, JAXA, launches the space explorer Hayabusa2 from the Tanegashima Space Center on a six-year-round trip mission to an asteroid to collect rock samples. The mission includes a main spacecraft, small rovers, a lander, and an impactor that will be launched into the asteroid’s surface to create an artificial crater. The spacecraft is expected to touch down on Ryugu multiple times starting in early 2019 to collect samples to bring to Earth in late 2020. - https://solarsystem.nasa.gov/missions/hayabusa-2/in-depth/NewsComAu

3 Dec 2019 - Indian amateur helps NASA reveal fate of failed moon mission, Shanmuga Subramanian A software engineer in the south Indian city of Chennai pored over satellite images in his spare time helped NASA locate the debris of India’s ill-fated mission to the moon. He looked at images of the moon’s surface on two laptops for six to seven hours a day until he found what he thought might be the debris of the moon lander. - https://www.washingtonpost.com/world/indian-amateur-helps-nasa-reveal-fate-of-failed-moon-mission/2019/12/03/4953b6fa-1592-11ea-bf81-ebe89f477d1e_story.html

Remembrances

3 Dec 1888 - Carl Zeiss, German scientific instrument maker, optician and businessman who founded the workshop of Carl Zeiss in 1846, which is still in business today as Carl Zeiss AG. Zeiss gathered a group of gifted practical and theoretical opticians and glass makers to reshape most aspects of optical instrument production. His collaboration with Ernst Abbe revolutionized optical theory and practical design of microscopes. Their quest to extend these advances brought Otto Schott into the enterprises to revolutionize optical glass manufacture. The firm of Carl Zeiss grew to one of the largest and most respected optical firms in the world. He died from a stroke at the age of 72 in Jena - https://en.wikipedia.org/wiki/Carl_Zeiss

3 Dec 1894 - Robert Louis Stevenson, Scottish novelist and travel writer, most noted for Treasure Island, Kidnapped, Strange Case of Dr Jekyll and Mr Hyde, and A Child's Garden of Verses. A celebrity in his lifetime, Stevenson's critical reputation has fluctuated since his death, though today his works are held in general acclaim. He is currently ranked as the 26th most translated author in the world. He died from a hemorrhagic stroke at the age of 44 in Vailima, Apia - https://en.wikipedia.org/wiki/Robert_Louis_Stevenson

3 Dec 1984 - Vladimir Abramovich Rokhlin, Azerbaijani and Soviet mathematician, who made numerous contributions in algebraic topology, geometry, measure theory, probability theory, ergodic theory and entropy theory. Rokhlin's contributions to topology include Rokhlin's theorem, a result of 1952 on the signature of 4-manifolds, which was subsequently generalised by Friedrich Hirzebruch. He also worked in the theory of characteristic classes, homotopy theory and cobordism theory. In measure theory, Rokhlin introduced what are now called Rokhlin partitions. He introduced the notion of standard probability space, and characterised such spaces up to isomorphism mod 0. He also proved the famous Rokhlin lemma. He died from a heart attack at the age of 62 in Leningrad - https://en.wikipedia.org/wiki/Vladimir_Abramovich_Rokhlin

Famous Birthdays

3 Dec 1857 - Joseph Conrad, Polish-British writer regarded as one of the greatest novelists to write in the English language. Though he did not speak English fluently until his twenties, he was a master prose stylist who brought a non-English sensibility into English literature. Conrad wrote stories and novels, many with a nautical setting, that depict trials of the human spirit during what he saw as an impassive, inscrutable universe. Conrad is considered an early modernist, though his works contain elements of 19th-century realism. His narrative style and anti-heroic characters have influenced numerous authors, and many films have been adapted from, or inspired by, his works. Numerous writers and critics have commented that Conrad's fictional works, written largely in the first two decades of the 20th century, seem to have anticipated later world events. Writing near the peak of the British Empire, Conrad drew, among other things, on his native Poland's national experiences and on his own experiences in the French and British merchant navies, to create short stories and novels that reflect aspects of a European-dominated world—including imperialism and colonialism—and that profoundly explore the human psyche. He was born in Berdychiv - https://en.wikipedia.org/wiki/Joseph_Conrad

3 Dec 1960 - Julianne Moore, American actress and children's author. Prolific in film since the early 1990s, she is particularly known for her portrayals of emotionally troubled women in both independent and Hollywood films, and has received many accolades, including an Academy Award and two Golden Globes. Time magazine named Moore one of the 100 most influential people in the world in 2015. Moore received considerable recognition in the late 1990s and early 2000s, earning Oscar nominations for Boogie Nights, she played a 1970s pornographic actress. She also had success with the films The Big Lebowski, Hannibal, Children of Men and Crazy, Stupid, Love, and won an Emmy Award for her portrayal of Sarah Palin in the television film Game Change. Moore won the Academy Award for Best Actress for her playing an Alzheimer's patient in Still Alice and was named Best Actress at the Cannes Film Festival for Maps to the Stars. Her highest-grossing releases include the final two films of The Hunger Games series and the spy film Kingsman: The Golden Circle. She was born in Fort Bragg, North Carolina - https://en.wikipedia.org/wiki/Julianne_Moore

3 Dec 1960 - Daryl Hannah, American actress and environmental activist. She is known for her roles as Pris Stratton in Ridley Scott's science fiction thriller Blade Runner and as Cathy Featherstone in Randal Kleiser's romantic comedy Summer Lovers, as the mermaid Madison in Ron Howard's fantasy-romantic comedy Splash, Roxanne Kowalski in the romantic comedy Roxanne, Darien Taylor in Oliver Stone's drama Wall Street and Annelle Dupuy Desoto in the comedy-drama Steel Magnolias. In 2015 she appeared in the Netflix series Sense8 as Angelica Turing. In 2004, Hannah won a Saturn Award for her role as one-eyed assassin Elle Driver in Quentin Tarantino's two-part martial arts action film Kill Bill. She was born in Chicago, Illinois - https://en.wikipedia.org/wiki/Daryl_Hannah

Events of Interest

3 Dec 1736 - Astronomer Anders Celsius takes measurements that confirm Newton's theory that the earth was an ellipsoid rather than the previously accepted sphere - https://www.onthisday.com/people/anders-celsius

3 Dec 1967 - 53-year-old Louis Washkansky receives the first human heart transplant at Groote Schuur Hospital in Cape Town, South Africa. Washkansky, a South African grocer dying from chronic heart disease, received the transplant from Denise Darvall, a 25-year-old woman who was fatally injured in a car accident. Surgeon Christiaan Barnard, who trained at the University of Cape Town and in the United States, performed the revolutionary medical operation. Even though he died 18 days later Washkansky’s new heart had functioned normally until his death. - https://www.history.com/this-day-in-history/first-human-heart-transplant

3 Dec 1992 – Neil Papworth, a test engineer for Sema Group uses a personal computer to send the world's first text message "Merry Christmas" via the Vodafone network to the phone of Richard Jarvis who was at a party in Newbury, Berkshire, which had been organised to celebrate the event. - https://en.wikipedia.org/wiki/Text_messaging#History

Intro

Artist – Goblins from Mars

Song Title – Super Mario - Overworld Theme (GFM Trap Remix)

Song Link - https://www.youtube.com/watch?v=-GNMe6kF0j0&index=4&list=PLHmTsVREU3Ar1AJWkimkl6Pux3R5PB-QJ

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