#Randomvariables

[randomvarious]

Today's compilation:

The Best of Rock 'N Soul 1988 Soul / Pop / Blue-Eyed Soul / Soft Rock / Pop-Rock

I mean, this is a decent set of 60s and 70s oldies hits overall, but the 'Rock 'n Soul' theme here is just way too loose, to the point that this selection actually feels almost entirely random. And I am deeply cognizant of the fact that my *own* name is randomvarious, but when I put those two words together, that doesn't mean that I want my various artist compilations to actually have random tracklists, because that's just really dumb and silly if you think about it.

Some pithy observations about this assortment of tunes, though: the two guys who'd end up becoming some of music's loudest anti-jab covid skeptics coincidentally lead this one off, with Van Morrison's "Brown Eyed Girl," and Eric Clapton's "I Shot the Sheriff." And Clapton's version of "I Shot the Sheriff" has always struck me particularly, because I guess I just really can't ever wrap my head around the fact that he first decided to cover this song that was originally by Bob Marley & The Wailers, and then went on a notoriously xenophobic and racist drunken rant on stage a few years later in which he hurled invective at an assortment of different groups, including Jamaicans, and said that they needed to be kicked out of Britain because Britain is a white country, while Marley himself was living there in exile. So the cognitive dissonance of this man's entire career is just really off the fucking charts to me, given that most of his life's work itself is rooted in the blues too 😬.

Next, I'm always flabbergasted by the voices of both Stevie Winwood and Alex Chilton whenever I hear early hits of theirs, like Winwood on "I'm a Man" by The Spencer Davis Group, and Chilton on "The Letter" by The Box Tops. Winwood recorded "I'm a Man" when he was just 18 years old and Chilton recorded "The Letter" when he was only 16, but both of them sound significantly older, with Winwood being blessed with an ability to soulfully bellow and Chilton able to apply a grizzled and raspy-throated ruggedness to his voice. Really remarkable on both fronts.

And then lastly, glad to see UK pop-soul and R&B group The Foundations on an American-made V/A comp like this with something other than "Build Me Up Buttercup." "Baby Now That I Found You" is a really catchy one, and if you love "Build Me Up," you'll probably love this one too and its super upbeat Carolina beachy vibe😎. It was their debut single and earned itself a top-15 placement on the US Billboard Hot 100, but obviously it's been overshadowed since; it's not nearly the same dynamic in the UK, however, where it went to #1 and "Build Me Up" went to #2.

So, some plenty good and classic tunes here, but no real coherent reason to have them all grouped together like this. And it also feels particularly crazy to consider a few of these as the best of what rock and soul had to offer too—basically, I'm looking squarely at you, "Baby Hold On to Me" by Eddie Money! 👀

Highlights:

Van Morrison - "Brown Eyed Girl" Eric Clapton - "I Shot the Sheriff" The Spencer Davis Group - "I'm a Man" The Box Tops - "The Letter" Righteous Brothers - "You're My Soul & Inspiration" Bill Medley - "Brown Eyed Woman" The Foundations - "Baby Now That I Found You" Music Explosion - "Little Bit O' Soul"

[upst--rs]

@randomvarious So this is the mix that I got. Just exported my favorites. 🤔

[praziluk]

was tagged by @389 to post an image of stuff ive been listening to recently.... ive mostly been listening to records so i was careful with the images i chose otherwise bill here would look rather silly lol. ive mostly been listening to schranz and hardgroove so here's some quality dj mixes ive enjoyed ^_^

i tag @therazgar @randomvarious @maeonline ... ok thank you

[davaulthunter]

Found this album thanks to @randomvarious !

[thebonesofhoudini]

"Somehow, by incorporating the strengths of both Techno and House music, Tech House succeeded by appealing to neither."

- @randomvarious

[hana--studies]

think this coffee shop would notice if i stole their wallpaper? need it.

[significant-stats-blog]

Probability, Random Variables and writing sample space #samplespace #probability #randomvariables #probabilityandstatistics #statistics #stats https://www.instagram.com/p/CAIquHrAt9f/?igshid=16qgacti66ssx

[codingbrewery-blog]

Maths 101 : Part 6: Measuring relationship between two Random Variables

Suppose you have taken the data for heights and weights of students in class and you want to figure out the correlation between heights and weights of students. The relation between these two parameters is defined mathematically by one of the 3 ways 1) Covariance 2) Pearson Correlation Coefficient 3) Spearman's rank correlation coefficient Each of these metrics has its own pros and cons so let's dive deeper into them.   Covariance Covariance is a measure of the joint variability of two random variables. If the greater values of one variable mainly correspond with the greater values of the other variable, and the same holds for the lesser values, (i.e., the variables tend to show similar behavior), the covariance is positive. In the opposite case, when the greater values of one variable mainly correspond to the lesser values of the other, (i.e., the variables tend to show the opposite behavior), the covariance is negative. The sign of the covariance, therefore, shows the tendency in the linear relationship between the variables  

In case we want to the covariance of a variable with respect to itself, it is always zero.   A simple way to understand covariance is by using this graph as an example

In this we can see stock market returns increase as economic growth increases and vice versa, hence we can say these two are positively correlated. Further gasoline prices and world oil production decrease as the other increase and we can say they are negatively correlated. The reason why monotonically increasing seems to have positive covariance is because for any point they will be either above mean or below mean and hence make overall covariance +tive. Note 1) The magnitude of covariance has nothing to do with the amount of overlap. Let's say something has a covariance of 5 doesn't mean anything. In fact, even if we change the units of heights and weights from cms to feet, lbs to kgs the covariance for the same dataset will change. What if we standardize the datasets before applying covariance, that becomes correlation and that can tell how much the data is correlated. 2) However, if there are outliers in the dataset, we may have a situation where covariance is -time for monotonically increasing relation. Pearson correlation coefficient The Pearson correlation coefficient (PCC), also referred to as Pearson's r, the Pearson product-moment correlation coefficient (PPMCC) or the bivariate correlation, is a measure of the linear correlation between two variables X and Y. Owing to the Cauchy–Schwarz inequality it has a value between +1 and −1, where 1 is the total positive linear correlation, 0 is no linear correlation, and −1 is the total negative linear correlation

  ρ =1 when there is a positive and perfect correlation. A naive example of this would be the height of a group of individuals in cms and inches. 0 Read the full article

[randomvarious]

Anyone know any good music substacks to follow? Downloaded the app yesterday and am looking for stuff to read now. Feel free to promote your own if you have one. I haven't posted anything there yet but I'm @randomvarious ✌️

[upst--rs]

Up to track 44 now of this 3 1/2 hour set. I am just supremely impressed with it. @randomvarious You might want to check this out sometime. Nobody is covering Russian jams. 😆

Seven tracks into this playlist of fifty, and so far it is just absolutely lit ... it's also got some, you'd think, uncharacteristic funk to it which is also amazing? 🤯

[myimaginaryradio]

Born To Run - Bruce Springsteen - 1975

I would like to send this out to @decadentpeacecherryblossom @turnsyourlifeintofolklore13 @docmart2016 @avi16 @evanptrss @randomvarious @usafcali @horsegirl thanks so much for following.

[getdownsaturdaynight]

Rules: Put your favorite Playlist on shuffle and then list the first ten songs and then tag ten people.

EXID - Ah Yeah

Earth, Wind, and Fire - Let’s Groove

Delegation - Darlin’ (I Think About You)

Justin Martin & Ardalan - LEZGO

Raito - One Step Beyond

Disclosure ft. Lorde - Magnets (VIP)

Justice - Genesis

Lady Gaga ft. Ariana Grande - Rain On Me

Haywyre - Storyteller

Redlight - City Jams

tagged by: @xhentai-man

tagging: @plushietoon @hoaegya @maeumerror @ironpaladont @gexshik @zeroescape @cardsgamesonmotorcycles @afrophvnk​ @randomvarious and anyone else who wants to do it! I wanna talk to more of y’all sometime.

[desertedvault]

thank you to @randomvarious who scours techno compilations for bangers

[codingbrewery-blog]

Maths 101 : Part 6: Measuring relationship between two Random Variables

Suppose you have taken the data for heights and weights of students in class and you want to figure out the correlation between heights and weights of students. The relation between these two parameters is defined mathematically by one of the 3 ways 1) Covariance 2) Pearson Correlation Coefficient 3) Spearman's rank correlation coefficient Each of these metrics has its own pros and cons so let's dive deeper into them.   Covariance Covariance is a measure of the joint variability of two random variables. If the greater values of one variable mainly correspond with the greater values of the other variable, and the same holds for the lesser values, (i.e., the variables tend to show similar behavior), the covariance is positive. In the opposite case, when the greater values of one variable mainly correspond to the lesser values of the other, (i.e., the variables tend to show the opposite behavior), the covariance is negative. The sign of the covariance, therefore, shows the tendency in the linear relationship between the variables  

In case we want to the covariance of a variable with respect to itself, it is always zero.   A simple way to understand covariance is by using this graph as an example

In this we can see stock market returns increase as economic growth increases and vice versa, hence we can say these two are positively correlated. Further gasoline prices and world oil production decrease as the other increase and we can say they are negatively correlated. The reason why monotonically increasing seems to have positive covariance is because for any point they will be either above mean or below mean and hence make overall covariance +tive. Note 1) The magnitude of covariance has nothing to do with the amount of overlap. Let's say something has a covariance of 5 doesn't mean anything. In fact, even if we change the units of heights and weights from cms to feet, lbs to kgs the covariance for the same dataset will change. What if we standardize the datasets before applying covariance, that becomes correlation and that can tell how much the data is correlated. 2) However, if there are outliers in the dataset, we may have a situation where covariance is -time for monotonically increasing relation. Pearson correlation coefficient The Pearson correlation coefficient (PCC), also referred to as Pearson's r, the Pearson product-moment correlation coefficient (PPMCC) or the bivariate correlation, is a measure of the linear correlation between two variables X and Y. Owing to the Cauchy–Schwarz inequality it has a value between +1 and −1, where 1 is the total positive linear correlation, 0 is no linear correlation, and −1 is the total negative linear correlation

  ρ =1 when there is a positive and perfect correlation. A naive example of this would be the height of a group of individuals in cms and inches. 0 Read the full article

[wolframtap]

th=1;s=Sqrt[2];dt=.01;tm=5;t=Range[0,tm,dt];U[a_,mu_,x0_]:=Module[{x=ConstantArray[0,Length[t]]},x[[1]]=x0;Do[x[[i]]=x[[i-1]]+th(mu-x[[i-1]])dt+s Sqrt[dt]RandomVariate[NormalDistribution[]],{i,2,Length[t]}];x];ListLinePlot[{U[9,0,9],U[0,0,0],U[-9,0,-9],U[0,-9,0]}]

https://twitter.com/wolframtap/status/1637222628229251075

[upst--rs]

I posted 180 times in 2022

103 posts created (57%)

77 posts reblogged (43%)

Blogs I reblogged the most:

@showandtelltime

@randomvarious

@upst--rs

@posthumanwanderings

@vgadvisor

I tagged 149 of my posts in 2022

Only 17% of my posts had no tags

#music - 33 posts

#cyberpunk 2077 - 22 posts

#cd projekt red - 21 posts

#electronic - 13 posts

#cp2077 - 12 posts

#johnny silverhand - 12 posts

#poetry - 9 posts

#punk - 9 posts

#spilled ink - 8 posts

#alt rock - 8 posts

Longest Tag: 49 characters

#♫alll we neeed is jusst a litttttle pattttiencce♪

My Top Posts in 2022:

#5

143 notes - Posted September 3, 2022

#4

When you’re catching up with a friend who’s become transgender since the last time you saw them.

177 notes - Posted October 19, 2022

#3

195 notes - Posted August 19, 2022

#2

A reasonable thesis ...

197 notes - Posted August 15, 2022

My #1 post of 2022

I’ll take ‘things you definitely don’t want to hear during sex’ for $500, Alex.

422 notes - Posted August 26, 2022

Get your Tumblr 2022 Year in Review →

This used to be a poetry blog lol. Also, in my ten years on this hellscape, used tumblr more in 2022 than ever. All the hot chick socials have become corpulent, porcine masses filled with masses, but this place is still cool. 😎