Regression: Crash Course Statistics #32

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Today we're going to introduce one of the most flexible statistical tools - the General Linear Model (or GLM). GLMs allow us to create many different models to help describe the world - you see them a lot in science, economics, and politics. Today we're going to build a hypothetical model to look at the relationship between likes and comments on a trending YouTube video using the Regression Model. We'll be introducing other popular models over the next few episodes.

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This series is amazing! I have majored in Statistics and still this series explains everything much better than college classes.

justynaizabela

I swear this series is the reason I am actually doing well in statistics! Wish I had this in my BSC (MSc Student)

sarlut

I think you guys are the reason people study or stay in school. net positive for humanity. thanks for helping people.

theidiotboy

These graphical presentations are so good, especially at 8:30 the didferent sums of square types

benbernanke

This course is sooo good. I'm using the Covid-19 Quaratine to educate myself in Statistics and this Crash Course was THE finding. Thanks a lot!

raposo_debora

This is great, especially the explaination of degrees of freedom. I never really understood it through five years of Economics so thank you.

alfredgustafsson

This right here is the most entertaining and intriguing statistical video Ive ever watched.. it actually made stats fun, thanks for incorporating art and creativity to this piece, ,instead of old and boring numbers presented in a monotonic go to sleep now voice

dondacurator

the best thing about the video is how the pumpkin and the transformer slowly eat all the candy worms that were on the table during the video

klaras

Some unnecessarily confusing parts:

It would have been helpful to explain that our zero-coefficient line IS the line y='y hat'.

The point referred to at 7:05 is not highlighted or pointed out (and as it sits far above its distance for SSR it isn't instantly recognizable as connected).

Positioning of the equations at 8:50 gives strong and erroneous implication that each refers specifically to the diagram above.

The equation given for F-statistic at 8:58 is then instantly revised as not being correct.

The correct f-statistic equation is only on screen at 10:07 for a fraction of the time needed to read it - let alone fully digest it.

mws

She speaks a little too fast for me but clearly explained. I like it.

RaulPelcastreRealEstate

Only crash course can make statistics interesting. Thank you for making quality educational videos for free! :D

NN_

How can she keep speaking without inhaling!?

kanitoneko

NOTE: This video uses the abbreviation "GLM" incorrectly (or at least very misleadingly) throughout.

The general linear model is NOT usually what is meant by "GLM". Instead, GLM stands for generaLIZED linear model, which is a special kind of linear model that (among other things) allows for a response variable that is not normally distributed. (Yes, this is extremely confusing. Don't even get me started on the word "linear", which doesn't even mean "straight lines" in this context.)

Bottom line: substitute simply "linear model" whenever Adrienne says "GLM" in this video, and you'll be fine.

OlleLindestad

Interesting. I just factchecked the theory about the comment-to-likes ratio, and it met pretty well: At the time I've written this, there were 41 comments and 391 likes, which is just the value "4000/100" shown in the diagram... As it turned out, this time it's above the regression line, but with an increase in the y-value by less than 35%

seltsamerjunge

This series is pointless... until you actually need this stuff for class and then you're thankful to God that it exists. Thanks for everything y'all do!

expansivegymnast