#algebra substitution method

[9nid]

Mastering Special Series in Geometric Progression (7+77+777+... & 0.3+0.33+...) - Complete Guide

Geometric Progressions (GP) become fascinating when we encounter special series like: 7 + 77 + 777 + 7777 + … to n terms 0.3 + 0.33 + 0.333 + 0.3333 + … to n terms (and infinite terms) In this comprehensive guide (based on 9nid’s YouTube Video – Geometric Progression Part 3), we’ll break down:✓ The step-by-step method to solve these series✓ How to find sums for finite AND infinite terms✓…

[edusquaremaths]

Mastering Special Series in Geometric Progression (7+77+777+... & 0.3+0.33+...) - Complete Guide

Geometric Progressions (GP) become fascinating when we encounter special series like: 7 + 77 + 777 + 7777 + … to n terms 0.3 + 0.33 + 0.333 + 0.3333 + … to n terms (and infinite terms) In this comprehensive guide (based on 9nid’s YouTube Video – Geometric Progression Part 3), we’ll break down:✓ The step-by-step method to solve these series✓ How to find sums for finite AND infinite terms✓…

[quantix745]

Solving Linear Equation by Simple Method || Variables on both sides || Q...

[digitaldetoxworld]

7 Mathematics Problem Solving Strategies With Solutions Boost Your Learning

 Mathematics Problem Solving Strategies With Solutions isn't merely approximately solving problems but growing a systematic approach to address numerous demanding situations. Here, we'll discover some effective problem-solving techniques that can useful resource students and specialists alike in their mathematical endeavors.

 Understand the Problem

Mathematics Problem Solving Strategies For Students the first and most essential step is to very well recognize the hassle. Read the problem cautiously and pick out what is being asked. Break it down into simpler components if necessary. This might contain:

Restating the Problem

Rephrase the hassle on your own words to ensure comprehension.

Identifying Given Information

Note down what facts is supplied and what desires to be found.

Visualizing the Problem

Draw diagrams or graphs if the hassle is geometric or involves spatial reasoning.

 Devise a Plan

Once you recognize the hassle, formulate a approach to remedy it. There are diverse strategies you may take:

Choose a Strategy: 

Select the best strategy primarily based on the sort of problem. Common techniques include:

Direct Computation

Use formulas or algorithms to solve the trouble at once.

Backtracking:

Start from the solution and paintings backward.

Working Backwards

 Begin with the preferred outcome and determine the stairs had to reach it.

Divide and Conquer

Break the problem into smaller, extra workable components and clear up each part one at a time.

Pattern Recognition

Look for patterns or sequences which could simplify the problem.

Use Analogies: 

Relate the trouble to a comparable one you have solved before.

Develop a Step-through-Step Plan: 

Outline the steps you will take to solve the hassle, making sure each step logically follows from the previous one.

 Carry Out the Plan

Implement your preferred strategy and paintings through the hassle methodically. This section involves:

Executing Steps:

Follow the stairs mentioned on your plan. Be meticulous and double-check your calculations.

Keeping Track of Progress

Regularly assess whether or not you're transferring within the proper course. If you locate that the strategy isn’t running, be organized to revisit and revise your plan.

 Review and Reflect

After attaining an answer, take the time to review your work:

Verify the Solution: 

Check the outcomes to make sure they may be correct. Substitute your solution again into the original trouble if applicable.

Analyze the Process

Reflect on the approach you used. Consider if there has been a extra efficient way to remedy the trouble.

Learn from Mistakes

 If the answer is incorrect, pick out where the mistake happened and understand why. Learning from mistakes allows in improving problem-fixing talents.

Common Strategies for Different Types of Problems

Here’s the way to follow the above techniques to extraordinary forms of mathematical issues:

Algebraic Problems

Simplify the Expression: 

Combine like terms and simplify expressions as tons as possible.

Isolate Variables

Solve for the variable via isolating it on one aspect of the equation.

Check Solutions:

Substitute again into the unique equation to verify the solution.

 Geometric Problems

Use Formulas

Apply appropriate geometric formulas for area, quantity, and perimeter.

Apply Theorems: 

Utilize geometric theorems like Pythagorean theorem, residences of comparable triangles, etc.

Draw Diagrams: 

Accurate diagrams can offer insights and assist in visualizing the problem.

 Calculus Problems

Understand the Functions

Know the function’s behavior, inclusive of continuity and differentiability.

Apply Calculus Rules: 

Use differentiation and integration rules as it should be.

Check Limits

Verify limits and asymptotic behavior for more complicated troubles.

 Combinatorial Problems

Use Counting Principles: 

Apply essential counting principles like diversifications and mixtures.

Inclusion-Exclusion Principle: 

Use this principle for problems regarding overlapping units.

Generate Functions: 

Use generating features for complex counting troubles.

 Number Theory Problems

Use Divisibility Rules:

Apply regulations for divisibility to simplify the problem.

Explore Modular Arithmetic: 

Use modular mathematics for troubles involving remainders.

Use Theorems: 

Apply number concept theorems like Fermat’s Little Theorem or Euler’s Theorem.

 Practice and Persistence

Consistent exercise is prime to becoming proficient in problem-solving. Regularly have interaction with numerous issues to build and strengthen your talents. Additionally:

Study Different Approaches

Explore various strategies and answers to apprehend a couple of approaches to resolve a hassle.

Work on Real-World Problems

Apply mathematical standards to actual-world scenarios to enhance realistic understanding.

Collaborate with Others

Discussing problems with peers or mentors can provide new insights and techniques.

Tools and Resources

Utilize various equipment and sources to aid in trouble-solving:

Mathematical Software

Tools like MATLAB, Mathematica, or maybe on line calculators can help in performing complicated calculations and visualizing facts.

Books and Journals

Refer to mathematical textbooks and research journals for in-intensity factors and superior strategies.

Online Forums and Communities

Mathematics Problem Solving Strategies For High School engage with online math communities for aid and collaborative problem-solving.

[readingsquotes]

"This piece aims to identify the pitfalls in thinking about what is being called an ‘algorithmic genocide’ in Gaza. I’d like to push against the exceptionalism afforded to AI; for example pieces which set military uses of AI as distinct from previous iterations of techno-warfare. Rather, the spectre of ‘artificial intelligence’ is a reification—a set of social relations in the false appearance of concrete form; something made by us which has been cast as something outside of us. And the way in which AI has been talked about in the context of a potentially ‘AI-enabled’ genocide in Gaza poses a dangerous distraction. All of the actually interesting and hard problems about AI, besides all the math, lie in its capacity as an intangible social technology and rhetorical device which elides human intention, creating the space of epistemic indeterminacy through which people act.

...The data does not “speak for itself”, neither in the context of academic research or in military applications.

Any ML model is, from its beginning, bound to a human conceptual apparatus.

...

The reification of AI, which happens at all points on the political spectrum, is actively dangerous in the context of its being taken to its most extreme conclusion: in the ‘usage' of ‘AI’ for mass death, as in the case of Gospel (‘Habsora’, הבשורה, named after the infallible word of God) and Lavender. This reification gives cover for politicians and military officers to make decisions about human lives, faking a hand-off of responsibility to a pile of linear algebra and in doing so handing themselves a blank check to do whatever they want. The extent to which these “AI systems” are credible or actually used is irrelevant, because the main purpose they serve is ideological, with massive psychological benefits for those pressing the buttons. Talking about military AI shifts the focus from the social relations between people to the technologies used to implement them, a mystification which misdirects focus and propagates invincibility.

There are things which are horrifying and exceptional about the current genocide, but the deployment of technology is not in itself one of those things; the usage of data-driven methods to conduct warfare is neither ‘intelligent’ nor ‘artificial’, and moreover not even remotely novel. As prior reporting from Ars Technica has shown about the NSA’s SKYNET program in Pakistan, Lavender is not even the first machine learning-driven system of mass assassination. I recently read Nick Turse’s Kill Anything That Moves: The Real American War in Vietnam (2013) and was struck by the parallels to the current campaign of extermination in Gaza, down to the directed-from-above obsession with fulfilling ‘body count’ as well as the creation of anarchic spaces in which lower-level operatives are afforded opportunities to carry out atrocities which were not explicitly ordered, an observation which has also been made of the Shoah. Thinking about it in this way allows us to fold AI into other discourses of technological warfare over the past century, such as the US’s usage of IBM 360 mainframe computers in Vietnam to similarly produce lists of targets under Operation Igloo White. Using technology as rhetorical cover for bureaucratized violence is not new.

The Lavender piece by Yuval Abraham states that IDF soldiers rapidly rubber-stamped bombing targets “despite knowing that the system makes what are regarded as ‘errors’ in approximately 10 percent of cases”. But even if the error rate were 0.005% it wouldn’t matter, because the ‘precision’ canard is just laundering human intent through a justification-manufacturing apparatus which has zero technical component. Abraham reports that “sources who have used Lavender in recent months say human agency and precision were substituted by mass target creation and lethality,” but in reality exactly zero human agency has been removed. He writes that “once the list was expanded to include tens of thousands of lower-ranking operatives, the Israeli army figured it had to rely on automated software and artificial intelligence…AI did most of the work instead”, but this verbiage is a perverse reversal of cause and effect to create post-hoc justification.

...

Another line from the Gospel piece reads “the increasing use of AI based systems like Habsora allows the army to carry out strikes on residential homes where a single Hamas member lives on a massive scale”. Emphasis mine—that word ‘allows’ is the hinge upon which this whole grotesque charade rests. The algorithm isn’t choosing anything; the choices already happened in the compiling and labeling of the dataset. The collecting and categorizing of data—which data on individuals’ social media or GPS movements or purchasing activity is to be used, which to be excluded—is in itself the construction of an elaborate ideological apparatus."

..

The purpose of a system is what it does, and science is a thing which people do

...We can expect the laundering of agency, whitewashed through the ideological device of 'the algorithm', to begin to be deployed in the arena of international law, given the ways in which Israel is already trying to sidestep the ‘genocidal intent’ it has been charged with at the ICJ. "The fetish of AI as a commodity allows companies and governments to sell it, particularly Israel, which still enjoys a fairly glowing reputation in the ML/AI industry and research world."

[jonathankatwhatever]

Continuing but almost Erev Christmas, 2024. Is there a better way to describe, or rather is there a simple way to describe Observer distance? The generation of D3-4Space means contextual scale, means algebras within contextual scales, which may be determined independent of each other within enclosing contexts, which may or not be complete because this is a common or ubiquitous function.

So, as we’ve refined 50:50 until it has emerged as the organizing method by which the Actor experiences, down to the seamless but sometimes absurd nature of construction, then what is the Observer experience method? It has to be focus, right? At which counts, meaning Ends, meaning where Observer can appear, the potential for Observer to appear, et voilá a rabbit, is a fit. To be clear because this escapes my memory too often: when I type fit, I mean the CR process within a layer and Regularization across layers, where by layers I mean dimensions. So Regularization forms pentagonal and the orientation of the pentagonal is CR. You can squeeze these very close together, so close you can barely tell which causes which.

So the O-line consists of the counts along the orthogonal which organize, so associative and ordinal to the fit on the counting line. Note how much clearer cardinality is now: it’s what is included in the counts up to yay, a count of the counts. Comparison of cardinality makes a lot more sense.

Counts of 1 translate into gsPrimes, which means counts of many kinds.

You could say it’s a form of incompleteness: that contextual scale means incompleteness. As in, you can exist in an isolated cell or have a Fortress of Solitude but those walls are inside larger spaces. That’s Boundary, so this also becomes that contexts require Boundary and vice versa; just substitute the label Thing for Boundary and that’s easy.

I’m getting comfortable with this material.

Before I shut it off for the night, I had the most unusual experience at the gym, even for me: I was working through weighted cable wrist and hand movements, felt a strong tingle or twang in my left, and then it was gone. I wonder if it comes back. It’s part of the freedom increasing in the left side. And since then my hand has felt more alive, more fluid.

[topscoree]

NEET Physics Made Easy: How to Solve Complex Problems

Physics is often considered the most challenging subject in the NEET exam, yet it is also the one that can significantly boost your overall score. Tackling complex problems in NEET Physics requires not just knowledge but also strategy, practice, and confidence. In this blog, we’ll walk you through the steps to make solving those daunting Physics problems a breeze.

NEET Training in Coimbatore

1. Understand the Basics First

Before diving into complex problems, ensure your basics are rock-solid. Physics builds upon foundational concepts, so take the time to:

Master fundamental theories and formulas.

Grasp the derivations of key equations to understand their applications.

Review topics such as Newton’s Laws, Electrodynamics, Thermodynamics, and Optics in depth.

Pro Tip: NCERT textbooks are your best friend for building strong foundational knowledge.

2. Break Down the Problem

Complex Physics problems often appear overwhelming because they combine multiple concepts. Follow these steps to simplify:

Read the Problem Twice: Understand what is being asked and identify the given data.

Highlight Keywords: Look for terms that indicate specific concepts (e.g., "frictionless," "steady state," "ideal gas").

Sketch a Diagram: If applicable, draw a free-body diagram, circuit diagram, or ray diagram to visualize the scenario.

Example: For a projectile motion problem, sketch the trajectory and label initial velocity, angles, and forces.

3. Identify the Relevant Concepts

Once you break down the problem, pinpoint the concepts it involves. For example:

Is it a kinematics problem?

Does it involve energy conservation?

Are you dealing with rotational motion?

Write down the relevant formulas before proceeding to calculations.

NEET Coaching Centres in Coimbatore

4. Use a Step-by-Step Approach

A systematic approach is key to solving any Physics problem:

Step 1: List known variables and assign symbols to unknowns.

Step 2: Write down the governing equations.

Step 3: Substitute known values and solve algebraically.

Step 4: Verify the units and dimensions of your answer.

5. Practice Approximation Techniques

Physics problems in NEET often include lengthy calculations. Approximation can save time:

Round off constants (e.g., use g=10��m/s2g = 10 \, \text{m/s}^2g=10m/s2 instead of 9.89.89.8).

Simplify fractions for quick mental math.

Pro Tip: Practice Vedic math or shortcuts to speed up calculations.

6. Time Management Matters

While solving problems during practice, focus on efficiency:

Allocate a set time to each question.

Use a timer to mimic exam conditions.

Skip and revisit questions if you get stuck.

7. Master Previous Year Questions

A significant portion of NEET Physics questions is inspired by previous years' papers. Make it a habit to:

Solve previous 10 years’ questions.

Note recurring patterns or frequently tested concepts.

Reflect on your mistakes to prevent repeating them in the future.

NEET Training in Coimbatore

8. Use Shortcuts Wisely

Memorize key formulas, but also learn derivations for when you need to tweak them. For example:

In mechanics, memorize work-energy theorem shortcuts.

In electrostatics, remember simple tricks for charge distribution.

9. Leverage Mock Tests

Mock tests are the ultimate preparation tool:

Simulate exam conditions.

Review the solutions thoroughly, focusing on where you went wrong.

Learn alternative methods from detailed solutions.

10. Stay Calm and Confident

Physics problems can be tricky, but they are not unsolvable. Maintain a positive attitude and avoid overthinking. During the exam:

Start with easy questions to build momentum.

Tackle challenging problems after ensuring accuracy in simpler ones.

NEET Coaching Centres in Coimbatore

Quick Recap: Physics Problem-Solving Checklist

Understand the basics thoroughly.

Break the problem into smaller parts.

Identify relevant concepts and equations.

Solve step-by-step and verify dimensions.

Practice regularly and analyze your errors.

With these strategies, you can conquer even the most complex NEET Physics problems. Remember, consistent practice and a clear understanding of concepts are your keys to success. Happy studying, and good luck with your NEET preparation!

[erikabsworld]

Understanding and Solving MATLAB Assignment Questions: A Step-by-Step Guide

MATLAB assignments in university often test complex topics that require both theoretical understanding and practical application. In this blog post, we will delve into one such challenging topic and provide a detailed guide on how to approach and solve a typical MATLAB assignment question. This will not only help you grasp the concept better but also equip you with the skills to tackle similar questions in your coursework.

Concept Overview: Gaussian Elimination Using MATLAB

Gaussian elimination is a fundamental method in linear algebra used to solve systems of linear equations. It involves transforming a system of equations into row-echelon form to easily solve for the variables. In MATLAB, this process can be automated using matrix operations and functions, making it efficient for solving large systems.

Sample Assignment Question: Solving a System of Equations

Question: Given the system of equations:

2x+3y−z=1 4x+y+2z=3 x+2y+3z=7

Use MATLAB to:

Formulate the coefficient matrix AAA and the constant vector bbb.

Solve the system using Gaussian elimination implemented in MATLAB.

Verify the solution by substituting back into the original equations.

Step-by-Step Guide to Answering the Question

Step 1: Formulating the Coefficient Matrix and Constant Vector

Begin by setting up the coefficient matrix A and the constant vector bbb.

Step 2: Solving the System Using Gaussian Elimination

Apply Gaussian elimination to solve for x, y, and z. This involves transforming the augmented matrix [A | b] into row-echelon form by performing row operations systematically.

Step 3: Verifying the Solution

Once you have obtained x, y, and z, verify the solution by substituting these values back into the original equations to ensure they satisfy all equations simultaneously.

How We Help Students

At matlabassignmentexperts.com, we specialize in guiding students through complex MATLAB assignments like Gaussian elimination. Our team of experienced MATLAB assignment doers ensures that students not only understand the concepts but also excel in their assignments. Whether you need assistance in understanding the theoretical aspects or require step-by-step solutions to MATLAB problems, our experts are here to support you.

Conclusion

Mastering MATLAB assignments, especially those involving concepts like Gaussian elimination, requires a blend of theoretical knowledge and practical skills. By following the systematic approach outlined in this blog post, you can confidently tackle similar MATLAB assignment questions and achieve academic success. Remember, matlabassignmentexperts.com is your reliable partner in navigating challenging assignments and securing top grades.

[eeveearoace]

so you love math, huh? name every method of integration

this is a love language. to me

it's been a little while since i've taken calculus, but i remember there's u-substitution and integration by parts. i'm taking statistics with calculus next semester, so i should probably do some calc review before then. hm...

but i've been working with matrices a lot recently <3 linear algebra my beloved (even if matrix multiplication still doesn't make sense. like. i know how to do it. but i don't get why it does the thing! agh!)

[cattutorialsblogs]

CAT Quantitative Aptitude: Preparation Tips, Practice, Strategy!

Quantitative Aptitude is a large thing of the CAT Exam, the section includes 22 questions based on blended concepts of basic mathematics. Students who are susceptible in this section regularly believe in positive myths approximately the CAT Quantitative aptitude. So earlier than discussing the education approach, we are able to bust a number of the most common myths approximately the CAT Quantitative Aptitude phase. Get a expert tips from Best Online Coaching for CAT.

Myths Around CAT Quantitative Aptitude Preparation

The CAT Quantitative Aptitude Section incorporates topics from the simple mathematics that we studied in Class ninth and 10th. One want now not be an professional in mathematics to attain well on this section. Understanding the fundamentals is believed to be the key to this section. It doesn’t rely how appropriate or horrific your Mathematics rating was. The secret's to capitalise on the expertise of the essential ideas and research their software in exclusive scenarios. If your Maths isn’t strong at the start of CAT education, with committed exercise, you could improve this segment by the point of the exam.

Completing the syllabus is greater crucial than practice.

Completing the syllabus is probably essential, however without practice, it is of no need. Many college students in no way start practising, because they are involved approximately the syllabus of entirety. As you study a brand new idea, you have to observe it in practice.

CAT Quantitative Aptitude is easier for Engineering heritage students.

CAT is an inherent ability-primarily based examination, which calls for sturdy logical and analytical talents. Anybody whose logical and analytical capabilities are robust or every person who can broaden them over a period of time can crack the CAT exam with high scores, no matter their academic heritage. Aspirants from Engineering backgrounds can also have sure blessings over non-engineering aspirants, but the examination is not easy for them either.

Prepare Arithmetic and you are ready for CAT Quantitative Aptitude.

There is not any doubt that Arithmetic is the important chunk of the Quants, which you can’t pass if you want to attain nicely within the Quant section. Every year you possibly can witness 8 to ten questions from mathematics within the CAT Quants segment. But it doesn’t imply that one must solely rely on Arithmetic, as in the end CAT is an unpredictable exam. Hence one should try to cowl the entire syllabus, as it increases your risk to score better in the exam.

Revision manner, virtually revising the method and concepts.

Revision of CAT Quantitative Aptitude isn't always just like the usual idea of revision. Here one does now not need to really revise the formulas, as a substitute one wishes to exercise questions of the previous topics for you to continue to be efficient in the particular subjects.

After busting the myths, allow us to now discuss a number of the most commonplace problems faced by aspirants in CAT Quantitative Aptitude Preparation.

Problems Faced in CAT Quantitative Aptitude

The Quants segment exams your mathematics competencies however no longer inside the way it became examined within the faculty days. It includes subjects like Arithmetic, Algebra, Geometry, and Modern Math. While these can also sound acquainted, the questions are crafted to measure competencies that managers want of their day-to-day paintings. Take CAT Online Coaching Classes for solve all your problems.Here we've got indexed a number of the maximum common issues aspirants face in this section.

Not selecting the proper questions.

The paper setters of the CAT Exam have mastered the art of making a good blend of clean and hard questions. When you go through the past year’s CAT question papers, you'll observe that there are some easier questions that could take only a few seconds to resolve! On the alternative hand, there might be some questions that is probably pretty hard to crack, at least in the given time constraints. The purpose for having such a mix of questions is to check the time management abilties and selection capabilities of the candidates. As an awesome manager, you will want first to goal the low-hanging end result inside the examination.

In order to perform well inside the exam, you want to grasp the artwork of selecting the right set of questions to attempt. You ought to first strive the less complicated ones and then cross on trying the medium to tough ones depending upon the time left with you. The purpose for such an method is to maximize your attempts. CAT will not reward you with greater marks for solving hard questions. Hence you have to purpose to remedy as many questions as you can.

Not being thorough with the principles.

Most of the time, you may look at that you have been not able to resolve some questions even after you knew the idea. This is a hallmark of the fact that either you do now not understand the idea nicely or that you aren't well versed within the idea utility talents. Therefore, it's miles continually really helpful to be thorough with the standards. Practice plays an important function in idea clearance. Always make sure that you recognize the principles to the middle and spend an good enough quantity of time information the standards during the initial segment of your practise. Once you have understood the concept nicely, exercise questions related to it. Practising questions enables in solidifying your standards further.

Bad time management.

Bad time management is one of the maximum not unusual mistakes that candidates make in the CAT quants section. Sometimes, trying a single question brings a large difference in the CAT percentiles of candidates. Therefore, exact time management is important for cracking the quants segment in CAT.

Always control your time in any such way that you could undergo all the questions in the quants segment. One’s time management competencies can enhance by way of taking full-period exercise exams and mocks. Moreover, one ought to continually ensure that they do no longer depart smooth questions for the cease time. This might also result in useless panic and nervous conditions for you, and you may lose out on some less complicated questions.

Not analyzing questions carefully.

Not analyzing a query carefully might bring about a loss of time throughout the exam. Like, suppose you read a query incorrectly because of that you invested ten mins to clear up a question, that you can have solved in 5 mins or perhaps less than that.

As you already know, time is a constraint within the CAT examination. Candidates are continually in a rush to clear up as many questions as they can inside the quants sections. But one should usually try and study the questions well in conjunction with cautiously noting down the information from the query. You do not need to lose out your valuable time on stupid errors. Moreover, one ought to pay properly interest even as solving questions related to complicated calculations.

CAT Quantitative Aptitude Strategy

The CAT Quants phase is considered to be the highest-scoring section in the CAT exam. Planning and executing the right CAT Quants approach let you with getting a 99%le within the CAT Quantitative Aptitude phase. Given beneath are a few ought to-comply with recommendations for the CAT Quants phase.

Brush up your fundamentals:

This is the maximum important part of the examination. The syllabus of the CAT Quantitative Aptitude segment is confined to up to elegance 10 stage primarily based on past tendencies. Like in the iQuanta CAT 2024 Course a student is first supplied with Non-engineers videos which cowl fundamental-arithmetic from magnificence 6th to 10th. However, the application-based questions of those fundamental ideas can be difficult to try. This is why it is advocated that you whole your basics first and slowly flow on to training the exclusive packages of these fundamental standards. This is the most critical method for CAT Quantitative Aptitude. At first, it is probably hard to put your theory into exercise, however with time it's going to come without problems to you- one of the reasons why practicing is critical, in particular so for the quant segment.

Quick calculation:

It is very obvious which you need to have your calculation recreation robust for an powerful quants method for the CAT test. Even in case you are furnished with a calculator for the CAT Exam, this does not take away the requirement of mental calculation due to the fact massive time may be wasted in using the digital calculator since it isn't very consumer-friendly. So make sure which you are capable of carry out fairly less difficult calculations on your mind itself.

Practice:

No different CAT Quantitative Aptitude strategy can take away the function of exercise. When you get into the addiction of practicing your already memorised principles, you may create more potent neural connections for your brain that store these concepts to your lengthy-time period memory. Therefore, exercise as plenty as you can. You will also be able to build a habit of solving CAT Quant questions for prolonged durations, for this reason helping you teach your brain to resolve complicated calculations without feeling mentally drained. Thus, working towards will help you in building lengthy-term memory in addition to supporting you construct stamina for the examination.

Move successively:

Make positive which you pass from fundamental/less difficult standards to greater challenging ones in CAT quants. This manner, a logical flow could be maintained as simpler concepts are frequently employed to solve tough ones. Therefore, for example, it isn't suggested which you first put together for ‘Profit and Loss’ before mastering the basics of the Number System in Quants. This point ought to be truly stated on your CAT Quants instruction strategy.

[catmomjudy]

What’s even crazier is that:

Abby = token dispatcher (for more varied storytelling) + love interest

Maddie and Eddie entered the series at the same time as replacements for the main cast hole left by Abby’s departure.

Using the dreaded substitution methods of algebra:

If Abby = TD + LI

And Abby = Maddie + Eddie

And Maddie = TD

Then what does Eddie equal?

Do the math.

looking back it is really crazy that they got rid of Buck's love interest and then they wrote in a new character, Eddie Diaz, whose entire introduction revolved around Buck and being extremely hot

[britbrat16678]

Just wrote my second discussion for my class this month, it's College Algebra,

Here it is:

The best method that I would say works best for me is substitution. It was always easier for me especially when I learned this in high school. And I think that this was the same method that I used in high school that I preferred. But with math it isn't always one method that works there are many and each for a different purpose and to create a different output or the same. With these methods generally each takes a different approach to solving the equation. To me its all about the way that you comprehend and learn to use the method. It could be confusing and it could be explained many ways on how to use it or how to get to the solution. I think with my learning at least in math that I need a way that is straight and to the point, explains in a more basic way and is very clear. I feel it confuses me also when the book says it different, the professor says it different and an external source says it different. Because it jumbles it and creates confusion for me. I don't think currently in my life that this could be applied but I do know all the math together will allow me to become better in my career. With programming it's a lot of problem solving. While I have not learned fully in depth how these processes would be applied to the things i would do or how it would benefit, from the short class that i took on foundations of computer science it gave me perspective. It touched very briefly on how simple equations such as addition are used in programming to figure out a binary code. Although that binary code is low level programming allow the computer to understand exactly what we need it to perform. And a lot of the times this wasn't the case, the computer could only do simple equations and didn't have as much memory or cache and ran very slow. And even in earlier times the computer was ran by switches in a room and this room was dedicated to housing the computer. I've also learned that while a lot of general education courses are required for the completion of a degree some of the concepts that are gone over especially in math are used rather than the actual simplification of an equation. It's rendered differently in a computer it's 1s and 0s rather than 0-9. And each combination of 0s and 1s in a specific way can create a certain command.

Here was the discussion question:

Think about the three methods that you have learned to solve these types of equations, graphing, substitution, and elimination.Respond to the following in a minimum of 175 words:Which method works best for you? Why?How do you think this method of solving problems can be applied to your current life or future career? Include at least one example. Refer to Ch. 3, “Systems of Equations,” for ideas.

I think I did pretty damn well because I never wrote a discussion post that long before and was able to relate it to past knowledge and not only that but begin to explain what method was my favorite.

[jonathankatwhatever]

It’s 20 Dec 2024. My stomach hurts. I found some movements yesterday that got deep into the core of the twist. One was with a cable extending from below: step away and let the weight of it pull you as though you are trying to pull it with that one arm. Rotate through your shoulder’s movement so you twist until you are aligned to do a biceps curls so the movement goes directly over your face as you twist again, this time to extend your arm as though you’ve thrown your arm and the object attached directly over your own body.

I want to translate something. Here’s an open tab: the Pockhammer symbol, which is apparently something having do with rising and falling factorials, which are what? Look up. So it’s x(x+1) up to x(x+(n-1), so up to the End generated at n-1, which means focus on what’s in that enclosure, what comes to that End, which becomes finite because we’ve labeled not n but n-1, where 1 attaches to infinity, and thus we count to and within Ends, have subtotals, because Attachment Theory describes the relationship of any Thing with any other, and that of course must be visible in the act of counting, in the methods of mathematics.

This does what? It makes a square of x times that bigger version of x, or at more at the level I need is a square and a count of x’s, so at each x, there’s a square and a count of x’s, and that is true up to whatever n-1 you count. I’m putting aside n is infinite because we’re counting back from that by using the n-1 concept. I don’t feel comfortable turning that into notation because it’s a basic method used everywhere. The shift from the infinite to the finite occurs in the construction of D3-4Space. Are you having trouble accepting that in some way or are you not entirely awake? A core concept is that grid squares are finite because Things generate within D-structure. That’s another way of talking about the space. You can’t expect to pull up with ease each one in each ordering you stumble on. That’s unfair to us. And you can substitute any answer for the word one because Attachment Theory really is that good.

That was fairly eloquent for not 6AM. You’re in my head.

So that’s rising for the +. The falling is x(x-1)…x(x-(n-1)). What does that do? Makes an area of any x and takes away, at least as an operation, that n-1 count of the x at that level. In gs, that would be the same drawing with a CM1 of the x as a square, and all the x with one layer showing the addition of n times x and the other showing the removal of n times x from that CM1. So rising is over CM1 and falling is within CM1.

That’s actually an interesting example of the idea: I was drawn to the idea of translating this form of factorial, left the tab open, so it was available when I happened by a few days ago, which pushed it to the forefront because it was useful and not closed. That all occurs within the n-1 End’s identification. Whatever x you got, right? Then you can make a mountain out of a molehill or a molehill out of a mountain, meaning you can maximize or minimize. And you can see in it the betting, the cost of odds, the payoffs and exchanges.

So the symbol is the label for the algebra which sums all the levels of the sequence for each n-1. Okay.

The math of imperfections.

[scary-anon]

@tis-i-lyney

For a. Shorter version

Algebra is finding numbers you don’t know, usually substituted with letters in place of the unknown numbers, through various different methods.

Can you do algebra?

Can I do what?

[themathblogofsashanova]

September 6, 2022: My Post to Coursera's Constructivism in STEM Class (I pulled in my previous blog on mathematical notation for inspiration)

Standstills in Mathematics Education: Getting Past the Intimidation of Mathematical Notation

In this paper, I will discuss Two Conceptions of Mathematical Notation by Anna Sfard at the University of Jerusalem. The environment in which the use of operational versus structural understandings of mathematical notation were used was a secondary school environment. Specifically for this paper, this secondary school constituted 96 students, ages 14-17. They were asked to “translate four simple word problems into an equation”. They were also “asked to come up with verbal prescriptions (algorithms) for calculating the solutions of the same problem”, respectively. Finally, the environment is one where the notion of concept is just developing. Operational proceduralism, or the use of the program, is the earlier stage of development that is installed as an avoidance mechanism according to the hypothesis of Sfard as a substitute for the nonverbal, spatial crystallized concepts behind mathematics. Computer programs often supplant symbolic algebraic notation for the students, who have trouble understanding the full static picture of “operations of the named sort occurring in all pasts, presents, and futures” represented by the mathematical notation. Therefore, the only further characteristic is an avoidance of the next developmental stage, a stage where many students often get stuck (including myself). 

The learning environment for the student must be avoidant for a reason. From my interaction with students in my extensive experience as a math educator, I know that avoidance in mathematics often comes from insufficient understanding. As these students are clearly still in the procedural explication/operational stage of understanding mathematics (they are still in the maze running it out), they have not yet themselves devised the full concept of the complete map of the system of many of the algebraic symbols. Therefore, though the symbols may be used, they are still trying to conceive of them verbally. We hear such understandings when math is compared to a language. However, we can see that math is explicitly stated to be nonverbal in the following; “Italians and Arabs in the 1600’s used ‘syncopated’ or verbal descriptions of functions up to that point, at which point a transition to symbolic algebra [which therefore is specifically and definitively nonverbal] began.” Slowly the transition from word to function, function and its product to operation, and operation to atemporal spatial representation of a “crystallized” function begins. What is often left behind in teaching, according to Sfard–being in particular an opinion with which I professionally concur–is the constructivity of the situation. Notations are presented erroneously in two ways, as 1) frozen, perfect facts and 2) as verbal statements. Both of these are in error. Notations are often still heated “under the hood”, where the name of the representation is still having its analytic “gerrymandered constituencies” voting self-elements in and out in the halls of mathematics according to their comprehensive powers when put into rigorous practice. 

Additionally, verbal statements usually are these very analytical definitions that are verbal and therefore do not challenge the student to engage in the nonverbal, spatial reasoning that makes symbolic reasoning so difficult. Essentially, the issue here is students do not know there is a sort of “code switching” going on in learning types, and therefore think their verbal comprehensive mechanisms are inadequate, when instead teachers should be teaching nonverbal/spatial through visuals like the unit circle, physical puzzles such as Hanayama lock puzzles, and other methods that introduce this type of reasoning. Therefore, to improve the environments for conceptual, representative, and symbolic understanding, procedural/algorithmic understandings should slowly be transitioned out of support and replaced with symbolic/spatial/visual reasoning. This means creating environments that are visually and symbolically rich, emphasizing maps as third order representation, like concept maps, electoral maps, or even watching auctions or real estate price changes in real time. In addition, physical puzzles like Hanayama brand lock-and-key type puzzles are very much encouraged. 

By emphasizing the development instead of the “immediate perfect comprehension” of mathematical symbols, such immediate comprehension of words can be expected of words but not of “named crystallized functions”. Once this is established as being the nature of a symbol in a developmentally patient and educated manner, students can begin to form the correct understanding and mode of approaching mathematical notation. They will stop being so frightened, scared, and without tools when they know their verbal reasoning is not insufficient, but simply the wrong mental position for the task. Specifically, classrooms must be designed to acknowledge the verbal shared ground, incubate from within the operational dance, and fly up with a freed a novel conception into the symbolic view constitutive of the mathematical heights.

Works Cited

Sfard, Anna. (1987). Two conceptions of mathematical notions: Operational and structural. Proceedings of the Eleventh International Conference for the Psychology of Mathematics Education. 3. 

[shangakarkumardas]

Summary upon Computer Science and Information Technology

The Computer is a man-made electronic programmable robot meant to sequentially and automatically carry out a sequence of arithmetic and systematic operations. Here, we are giving a summary of Computer Science and Information Technology which has covered every one the essentials of computers.

The Computer is a man-made electronic programmable robot meant to sequentially and automatically carry out a sequence of arithmetic and systematic operations. Here, we are giving a summary of Computer Science and Information Technology which has covered every one the essentials of computers.

Computer science focuses almost creating programs and applications, though recommend technology focuses concerning using computer systems and network IT professionals in addition to campaigning a dogfight as data analysts, computer preserve specialists, and data scientists

Information Technology (IT) is a broader showground that encompasses Computer Science and even programming. So can be both easier or harder. IT courses or majors tend to be broader but shallower than CS courses or majors tend narrower but deeper in that particular place.

Programming language theory and formal methods:

Programming language theory is a branch of computer science that deals with the design, implementation, analysis, characterization, and classification of programming languages and their individual features. It falls within the discipline of computer science, both depending on considering quotation to and affecting mathematics, software engineering, and linguistics. It is an alert research place, following numerous dedicated academic journals. Formal methods are a particular subsequent to-door to of mathematically based technique for the specification, go ahead and statement of software and hardware systems. The use of formal methods for software and hardware design is motivated by the expectation that, as in supplementary engineering disciplines, the theater takeover mathematical analysis can contribute to the reliability and robustness of a design. They form an important educational underpinning for software engineering, especially where safety or security is operating. Formal methods are a useful integrate with crime to software investigation past them in the future happening avoid errors and can with meet the expense of a framework for breakdown. For industrial use, tool preserve is required. However, the tall cost of using formal methods means that they are usually without help used in the get on your nerves of high-integrity and dynamism-necessary systems, where safety or security is of utmost importance. Formal methods are best described as the application of a fairly wide variety of speculative computer science nitty-gritty, in particular logic calculi, formal languages, android theory, and program semantics, but then type systems and algebraic data types to problems in software and hardware specification and publication.

Computer Systems Computational and systems processes:

Artificial severity (AI) aims to or is required to synthesize set sights on-orientated processes such as encumbrance-solving, decision-making, environmental getting used to, learning, and communication found in humans and animals. From its origins in cybernetics and in the Dartmouth Conference (1956), precious height research has been necessarily gnashing your teeth-disciplinary, drawing in description to areas of finishing such as applied mathematics, symbolic logic, semiotics, electrical engineering, philosophy of mind, neuropsychology, and social intelligence. AI is allied in the expertly-liked mind when robotic touch ahead, but the main auditorium of practical application has been as an embedded component in areas of software influence to the front, which require computational concord. The starting reduction in the late 1940s was Alan Turing's investigation "Can computers think? And the ask remains effectively unanswered, although the Turing test is yet used to assess computer output almost the scale of human intensity. But the automation of evaluative and predictive tasks has been increasingly wealthy as performing for human monitoring and charity in domains of computer application involving rarefied genuine-world data.

Computer visualization and graphics:

Computer graphics and visualization. Computer graphics is the scrutinize of digital visual contents and involves the synthesis and exploitation of image data. Psychotherapy is related to many added fields in computer science, including computer vision, image incline, and computational geometry, and is heavily applied in the fields of special effects and video games.

Sound and Image processing: Information can publicize you will the form of images, hermetic, video, or substitute multimedia. Bits of mention can be streamed via signals. Its processing is the central notion of informatics, the European view up for computing, which studies recommendation giving out algorithms independently of the type of opinion carrier - whether it is electrical, mechanical, or biological. This arena plays important role in flavor theory, telecommunications, warn engineering and has applications in medical image computing and speech synthesis, in the middle of others. What is the lower bound going around for the air unwell of sudden Fourier transform algorithms? is one of the unsolved problems in conservatory computer science. Academia: Conferences are important behavior for computer science research. During these conferences, researchers from the public and private sectors proficiency their recent feint and meet. Unlike in most new academic fields, in computer science, the prestige of conference papers is again that of journal publications. One proposed relation for this is the unexpected build taking place of this relatively new field requires terse evaluation and distribution of results, a task improved handled by conferences than by journals. Software engineering: Software engineering is the chemical analysis of designing, implementing, and modifying the software in order to ensure it is of tall feel, affordable, maintainable, and hasty to fabricate. It is reasoned access to software design, involving the application of engineering practices to software. Software engineering deals as soon as the organizing and analyzing of software, it doesn't just treaty with the foundation or build of accumulation software, but its internal conformity and child support. For example, software investigation, systems engineering, highly developed debt, and software exaggerate processes. Anything: Gottfried Wilhelm Leibniz's, George Boole's, Alan Turing's, Claude Shannon's, and Samuel Morse's eagerness: there are unaccompanied two objects that a computer has to concur moreover in order to represent "all" All the auspices of approximately any computable shackle can be represented using by yourself 0 and 1 (or any added bistable pair that can flip-flop in the middle of two easily distinguishable states, such as "an apropos the order of/off", "magnetized/demagnetized", "high-voltage/low-voltage", etc.).

Concurrent, parallel, and distributed computing:

Concurrency is a property of systems in which several computations are executing simultaneously, and potentially interacting once each appendage.[48] A number of mathematical models have been developed for general concurrent computation, including Petra nets, process calculi, and the Parallel Random Access Machine model.[49] When fused computers are linked in a network through using concurrency, this is known as a distributed system. Computers within that distributed system have their own private memory, and reference can be exchanged to achieve common goals.

Information theory:

Information theory, a neighboring door connected to probability and statistics, is associated with the quantification of opinion. This was developed by Claude Shannon to locate fundamental limits regarding signal doling out operations such as compressing data and going not far afield off from for the order of reliably storing and communicating data. Coding theory is the scrutiny of the properties of codes (systems for converting hint from one form to other) and their fitness for a specific application. Codes are used for data compression, cryptography, error detection and correction, and more recently than for network coding. Codes are studied for the strived for of designing efficient and adroitly-behaved data transmission methods.

Note:

The opening of punched cards into the adjunct engine was important, not unaccompanied as a more convenient form of control than the drums, or because programs could now be of unconditional extent, and could be stored and repeated without the problem of introducing errors in setting the robot by hand; it was important as well as because it served to crystallize Babbage's feeling that he had invented something in reality totaling, something much more than a following calculating robot." Bruce Collier, 1970. See the entry "Computer science" concerning Wikiquote for the records of this suggestion. The word "anything" is written in reference marks because there are things that computers cannot reach. One example is: to unadulterate the question if an arbitrary unadulterated computer program will eventually finish or run forever (the Halting problem).

See the entry "Computer science" concerning Wiki quote for the records of this suggestion. The word "anything" is written in reference marks because there are things that computers cannot reach. One example is: to unadulterated, the question of an arbitrary unadulterated computer program will eventually finish or run forever (the Broken problem)