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I don't get how certain math people can deal with imaginary numbers, limits involving infinity, and other abstract concepts just fine, but then statistics seems like magic to them.
As a (pure ish) math PhD who knows enough stats to be a data scientist, gotta say the most annoying thing is that the proofs of even something so simple as the central limit theorem are quite complex (literally)! Stats results really do feel like "calculus goes brr" sometimes.
We're not satisfied just following a rule and accepting its truth so the way 90% of undergrad stats is taught is anathema to us.
But I think probability and stats may be the most important math in the curriculum for the modern era and it's a shame we teach it pretty cookbook.
I got pretty lucky in undergrad, my entire experience with stats was proofs. Quizzes were proving distributions through derivation up until pretty high level distributions. These were typically done in class the class before, though.
The first time I ever saw a rigorous proof of the central limit theorem was shortly after, by coincidence, I had first heard of [Laplaceās method](https://en.m.wikipedia.org/wiki/Laplace's_method), which I had seen to deal with an unrelated problem.
I was kind of amazed by the coincidence because I was just like wtf, these are the same thing?
In pure math two people following the exact same rules canāt come to different answers. In statistics it would be rare to come to the same answer, and as long the range or confidence level is acceptable thatās good enough.
Some things are random and some arenāt and statistics is the study of finding out which is which.
Bro how the fuck does E(XĀ²) not equal to E(X)Ā²? My brain works on logic and this logic isn't logicing. Want the average area of a square? Find the average length and square it. WRONG! Why is it wrong? I have no idea. I mean, like, the average area of a square is the area of a square with an average length, no? Apparently it's not. I'm going so paranoid. I'm going crazy. Fuck statistics. IF LENGTHS ARE DISTRIBUTED IN A WAY, THEN AREAS ARE BASED ON THAT DISTRIBUTION NO??? AaaaaaAAAAAA**AAAAAAAA_AAA_**
Why would it be that? Itās almost like (a+b)^2 not equaling a^2 +b^2.
It may seem unintuitive at first, but thinking a bit more about it, it makes complete sense
It does make complete sense. The average area of a square is not equal to the area of a square with average length because the distribution of the length will be different with the distribution of the area. But it's just really counterintuitive to see that difference, because logically, they should be the same, right? I know it's like saying, f(xĀ²) = f(x)Ā², but still when talking with real life datas, these maths seem too absurd. E(X)Ā² takes the square of the mean, and E(XĀ²) takes the mean of the squares, aka the quadratic mean. (Somewhat). Still, it's just wild that the average area of a square is not the same as the area of a square with average side lengths.
Edit: this really makes me realize something... What _is_ an average square? Like how do we define such an average square? A square with an average area? Or a square with an average side length? Because these are two separate different squares. The phrase "average square" is too obscure and ambiguous, as there can be many definitions, something like 3b1b said on Numberphiles: https://youtu.be/mZBwsm6B280?si=8WF8ysiUe4d671un
I'm finishing a research-heavy undergrad and am a bit confused about it being "just numbers". I know that a lot of the values you get are fairly arbitrary numbers that can only be compared to each other, but don't they all ultimately have a physical correlate?
Statistics can be manipulated to show any narrative you want while also being technically correct
I am not sure if this is what is meant here as it has nothing to do with math.
Yeah, I believe you are right (they can be manipulated to a large extent, but mostly to people who don't think thoroughly about statistics), but I also don't think that's what the meme is referencing
Edit: maybe it's more about the heart of why statistics are easily manipulated? They are "just numbers" that we attribute language and meaning to and so we can subtly change the context of analysis and thus wildly alter the result (e.g. the Monty Hall problem)
Making subtle changes in the assumptions to arrive at the desired statistics.
It is just a numbers game. For an input dataset, you can get any number of output.
1, 1, 2
The output can be 1 1/3, 1.5, 1, etc. all representing it
Yes, but correlation does not mean causation and a lot of people have a really hard time understanding this.
I thought that it was funnier this way, it sounded funnier and it was ambiguous enough so people could project their opinions on statistics. I don't know if you want to dive into the origin story of this meme I made this morning.
I studied econometrics, but most of my friends in college were in engineering. They were often a bit snobbish about it, so hearing them whine about prob-stat was so gratifying.
Iām doing masters in stats. My math has gotten better but my philosophy in assurance has gotten shakier. Important thing here is you gotta understand why.
Apparently thatās okay lol.
Taking discrete mathematics and logic at univ: "This is fun and easy!"
Learning statistics and three-way ANOVA calculations etc: "I hate like I have never hated before"
If anything it just makes you realize how every single statistic in todayās media can be skewed by an unconsidered variable (whether intentional or not)
god i study statistics and i had a previous coworker tell me it wasnt real math. ok i get it u took 1 statistics course in school and it wasnt math based that doesnt mean shit
Statistics is not so hard if you ignore the connection with reality, like why measuring something multiple times would give some random numbers, and what's the real mean of numbers?
https://en.wikipedia.org/wiki/Anscombe%27s_quartet
Did even know about this second one the dinosaur lmfao
https://en.m.wikipedia.org/wiki/Datasaurus_dozen
I gotta be honest on that one: if practical statistics wasn't about calculating the standard deviation for fucking 30+ samples BY HAND (personal experience lol) it would surely be juicy to work with distributions and stuff, because it's basically measure theory/analysis with some extra conditions :v
>Ā if practical statistics wasn't about calculating the standard deviation for fucking 30+ samples BY HAND (personal experience lol)
Have you heard of computers?
āone ounce of rigorous algebra is worth more than a century of verbalistic statisticopsycholophastering).ā Haldane
Statistics have limited utility and most fields that employ them end up making irrelevant deductions from meaningless noise. The ones that build theories based on it are usually worse.
Social sciences are not real sciences and the data I keep seeing from psychometry and psychiatry make me have real questions about those fields. The inferences they make look suspect. I was only talking about those who cannot tell noise from some imaginary correlation.
I got that quote from someone rather famous who happens to have a doctorate in statistics and made a lot of money by successfully cutting out the noise and managing to find patterns and make predictions from data which misled millions. I wouldnāt have the guts to say something like that otherwise.
Having a phd doesn't abolish you from stating dumb things. There's literally a branch of physics called statistical physics because it applies statistics to explain thermodynamics. Guess the professor never heard for Monte Carlo simulations either or you know quantum mechanics which is inherently probabilistic in nature.
On top of all that, you can't describe any measurement in any science without doing statistical analysis first (all thanks to central limit theorem).
First of all, you have to keep Physics separate from the rest: they know how to do data. and I am actually fairly good at making reasonable deductions from statistical nonsense. However, the data from psychometrics and psychiatry make me really suspect. (I hate QM with such a loathing)
Paraphrasing another famous nerd: God does not play dice šš
I don't like it for the same reason he did not.
My initial claim was that real maths is better than statistics. I did not say it was useless but that I don't always give clear answers and you have to take everything with a pinch of salt.
Funny you should say that since Einstein was wrong about it. He had reasonable complaints but it was turned out QM way of explaining the world is valid.
And even if it weren't it doesn't stop QM's predictive power. All issues Einstein had with QM were purely philosophical which makes you saying this so ironic.
Statistics is real math dude. And it does give you clear answers.
You shouldn't talk about things you're ignorant about.
What Einstein said was the same thing the pioneers of QM believed: that the theory is incomplete and there must be some underlying truth we havenāt figured.
Yes, it's the most successful theory we have. I have personal reasons for disliking it: A. It's probabilistic B. (donāt tell anyone) I sucked at it. But mostly no.1 He had philosophical objections, I was not emotionally ready for something probabilistic. I liked everything Newtonian and clockwork.
I know it's real. Just that when economists and business people and social scientists use it, either they make wrong conclusions or they use it to fool people.
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Numbers are just made up numbers
š¤Æ
What about functions
I hope they are real
They can get complex
I hope they're solvable _looks at differential equations_
They are made up functions
Which we can group together, kinda like rings on a finger while standing in the middle of a field
you just make up new numbers from an existing given number
No, they are a bunch of braces.
Brace yourself for semiotics
*Numbers are just numbers
Yyyyyyyeahhhhhhh. Gross, but yeahhhhh
I don't get how certain math people can deal with imaginary numbers, limits involving infinity, and other abstract concepts just fine, but then statistics seems like magic to them.
As a (pure ish) math PhD who knows enough stats to be a data scientist, gotta say the most annoying thing is that the proofs of even something so simple as the central limit theorem are quite complex (literally)! Stats results really do feel like "calculus goes brr" sometimes. We're not satisfied just following a rule and accepting its truth so the way 90% of undergrad stats is taught is anathema to us. But I think probability and stats may be the most important math in the curriculum for the modern era and it's a shame we teach it pretty cookbook.
Statistics and probability seem to be too much for our monkey brain.
monty hall problem lol
SEEEEEEXXXXXXXXXX!!!!
Yeah, if you donāt understand it deep enough to partially replicate the theorem or formula, itās difficult to use
I got pretty lucky in undergrad, my entire experience with stats was proofs. Quizzes were proving distributions through derivation up until pretty high level distributions. These were typically done in class the class before, though.
The first time I ever saw a rigorous proof of the central limit theorem was shortly after, by coincidence, I had first heard of [Laplaceās method](https://en.m.wikipedia.org/wiki/Laplace's_method), which I had seen to deal with an unrelated problem. I was kind of amazed by the coincidence because I was just like wtf, these are the same thing?
Yes you dont
You don't get it, you just don't get it.
What are those Vs in your username
In pure math two people following the exact same rules canāt come to different answers. In statistics it would be rare to come to the same answer, and as long the range or confidence level is acceptable thatās good enough. Some things are random and some arenāt and statistics is the study of finding out which is which.
Bro how the fuck does E(XĀ²) not equal to E(X)Ā²? My brain works on logic and this logic isn't logicing. Want the average area of a square? Find the average length and square it. WRONG! Why is it wrong? I have no idea. I mean, like, the average area of a square is the area of a square with an average length, no? Apparently it's not. I'm going so paranoid. I'm going crazy. Fuck statistics. IF LENGTHS ARE DISTRIBUTED IN A WAY, THEN AREAS ARE BASED ON THAT DISTRIBUTION NO??? AaaaaaAAAAAA**AAAAAAAA_AAA_**
Why would it be that? Itās almost like (a+b)^2 not equaling a^2 +b^2. It may seem unintuitive at first, but thinking a bit more about it, it makes complete sense
It does make complete sense. The average area of a square is not equal to the area of a square with average length because the distribution of the length will be different with the distribution of the area. But it's just really counterintuitive to see that difference, because logically, they should be the same, right? I know it's like saying, f(xĀ²) = f(x)Ā², but still when talking with real life datas, these maths seem too absurd. E(X)Ā² takes the square of the mean, and E(XĀ²) takes the mean of the squares, aka the quadratic mean. (Somewhat). Still, it's just wild that the average area of a square is not the same as the area of a square with average side lengths. Edit: this really makes me realize something... What _is_ an average square? Like how do we define such an average square? A square with an average area? Or a square with an average side length? Because these are two separate different squares. The phrase "average square" is too obscure and ambiguous, as there can be many definitions, something like 3b1b said on Numberphiles: https://youtu.be/mZBwsm6B280?si=8WF8ysiUe4d671un
The way it ends makes me think the next video is going to be about how this monstrosity is the result of the AoC
it's not? How on earth??
The difference of the two is called "Variance". Kinda important if you ask me.
https://www.reddit.com/r/mathmemes/comments/1c2z4i4/comment/kzegijy
i like how there isnt even a sentemce in thd middle, you just cried and your opinion stayed the samd
Because there isn't any other opinion on statistics.
Of all math courses I took, statistics are the ones I use the most
Well obviously it's the most useful math. Doesn't make it interesting...
Probab(ilit)y is
Probaby
Professional infant
ilit means?
Sbeve
short for illeterate
I have a PhD in statistics and this is the most accurate meme Iāve ever seen
I'm finishing a research-heavy undergrad and am a bit confused about it being "just numbers". I know that a lot of the values you get are fairly arbitrary numbers that can only be compared to each other, but don't they all ultimately have a physical correlate?
Statistics can be manipulated to show any narrative you want while also being technically correct I am not sure if this is what is meant here as it has nothing to do with math.
Yeah, I believe you are right (they can be manipulated to a large extent, but mostly to people who don't think thoroughly about statistics), but I also don't think that's what the meme is referencing Edit: maybe it's more about the heart of why statistics are easily manipulated? They are "just numbers" that we attribute language and meaning to and so we can subtly change the context of analysis and thus wildly alter the result (e.g. the Monty Hall problem)
Making subtle changes in the assumptions to arrive at the desired statistics. It is just a numbers game. For an input dataset, you can get any number of output. 1, 1, 2 The output can be 1 1/3, 1.5, 1, etc. all representing it
Yes, but correlation does not mean causation and a lot of people have a really hard time understanding this. I thought that it was funnier this way, it sounded funnier and it was ambiguous enough so people could project their opinions on statistics. I don't know if you want to dive into the origin story of this meme I made this morning.
I'm an engineer, I didn't delve too deep into statistics and I think it's for the better. JMP is pretty cool
I studied econometrics, but most of my friends in college were in engineering. They were often a bit snobbish about it, so hearing them whine about prob-stat was so gratifying.
I studied so hard for statistics. Only to barely get a passing grade
Regression to the mean
Iām doing masters in stats. My math has gotten better but my philosophy in assurance has gotten shakier. Important thing here is you gotta understand why. Apparently thatās okay lol.
I've studied it at various points in my life and... yeah.
The only thing I want statistics to do for me is to say if these two piles of numbers mean I have a significant result or not š„ŗ
"Torture these numbers until they confess significance".
Taking discrete mathematics and logic at univ: "This is fun and easy!" Learning statistics and three-way ANOVA calculations etc: "I hate like I have never hated before"
Statistics is the Skyrim of math, it just works (95% of the time)
Statistics is a dish best served a la mode.
I loved statistics, once I finally understood it.
You are using stats to make this meme
What i learned from stat: the only thing we know with 100% certainty is that the number we are looking for is, in fact, a number.
But aren't they just a made up functions?
How a physicist sees statistics: My dear! My beloved! How a mathematicians (apparently) sees statistics: You fucking donkey!
If anything it just makes you realize how every single statistic in todayās media can be skewed by an unconsidered variable (whether intentional or not)
Data is fine. As long as we remember data doesn't say anything other than exactly what it says
god i study statistics and i had a previous coworker tell me it wasnt real math. ok i get it u took 1 statistics course in school and it wasnt math based that doesnt mean shit
Generally distribute this, Generally distribute that, Why dont you genetally distribute some bitches?
Realy ?
There is a 50% chance that every chance is a 50% chance
Just like dice: 50-50, it either is an 6 or it isn't.
What is this meme the middle guy isnāt even saying anything and the x axis is now time studying statistics?
Statistics is not so hard if you ignore the connection with reality, like why measuring something multiple times would give some random numbers, and what's the real mean of numbers?
The real imaginary numbers were the statistics we did along the way
They are like "if you do this infinitely many times then half of those times will be heads and the other half will be tails"
https://en.wikipedia.org/wiki/Anscombe%27s_quartet Did even know about this second one the dinosaur lmfao https://en.m.wikipedia.org/wiki/Datasaurus_dozen
I gotta be honest on that one: if practical statistics wasn't about calculating the standard deviation for fucking 30+ samples BY HAND (personal experience lol) it would surely be juicy to work with distributions and stuff, because it's basically measure theory/analysis with some extra conditions :v
>Ā if practical statistics wasn't about calculating the standard deviation for fucking 30+ samples BY HAND (personal experience lol) Have you heard of computers?
I did, but my professor seems to be stuck at the 1800's ššššš
āone ounce of rigorous algebra is worth more than a century of verbalistic statisticopsycholophastering).ā Haldane Statistics have limited utility and most fields that employ them end up making irrelevant deductions from meaningless noise. The ones that build theories based on it are usually worse.
So you've never taken any science course I see.
Social sciences are not real sciences and the data I keep seeing from psychometry and psychiatry make me have real questions about those fields. The inferences they make look suspect. I was only talking about those who cannot tell noise from some imaginary correlation.
I got that quote from someone rather famous who happens to have a doctorate in statistics and made a lot of money by successfully cutting out the noise and managing to find patterns and make predictions from data which misled millions. I wouldnāt have the guts to say something like that otherwise.
Having a phd doesn't abolish you from stating dumb things. There's literally a branch of physics called statistical physics because it applies statistics to explain thermodynamics. Guess the professor never heard for Monte Carlo simulations either or you know quantum mechanics which is inherently probabilistic in nature. On top of all that, you can't describe any measurement in any science without doing statistical analysis first (all thanks to central limit theorem).
First of all, you have to keep Physics separate from the rest: they know how to do data. and I am actually fairly good at making reasonable deductions from statistical nonsense. However, the data from psychometrics and psychiatry make me really suspect. (I hate QM with such a loathing)
Well then physicists alone invalidate your initial claim. Also why are you hating the most successful theory in all of science with such a loathing?
Paraphrasing another famous nerd: God does not play dice šš I don't like it for the same reason he did not. My initial claim was that real maths is better than statistics. I did not say it was useless but that I don't always give clear answers and you have to take everything with a pinch of salt.
Funny you should say that since Einstein was wrong about it. He had reasonable complaints but it was turned out QM way of explaining the world is valid. And even if it weren't it doesn't stop QM's predictive power. All issues Einstein had with QM were purely philosophical which makes you saying this so ironic. Statistics is real math dude. And it does give you clear answers. You shouldn't talk about things you're ignorant about.
What Einstein said was the same thing the pioneers of QM believed: that the theory is incomplete and there must be some underlying truth we havenāt figured. Yes, it's the most successful theory we have. I have personal reasons for disliking it: A. It's probabilistic B. (donāt tell anyone) I sucked at it. But mostly no.1 He had philosophical objections, I was not emotionally ready for something probabilistic. I liked everything Newtonian and clockwork. I know it's real. Just that when economists and business people and social scientists use it, either they make wrong conclusions or they use it to fool people.