Explaining generalized linear models (GLMs)

[@ubuntumaster]

You are a true educator, thank you for keeping my love strong for statistics in a time where uni and grad school often crushes your passions

[@gavinmcquilkin6620]

Intro just gave me a heart attack. Crazy rollercoaster but glad you’ll still be around!

[@xanmos]

This brought me back to my masters (statistics) days. Im happy to see the exponential family again. ❤ And hey, thanks for showing some simulation in R. Happy holidays too.

[@adityamwagh]

Hey! Don’t stop making videos. You’re doing a very important job! World needs people like you!

[@bigclout0056]

I was genuinely looking for a video explaining GLMs. Thank you!

[@fikrikeremkinal5254]

The equation at 9:42 says e^beta_0, but it should be e^beta_1, a friendly correction! Love the channel, thank you for the videos :)

[@123voorhees]

Honey, wake up! New very normal video just dropped!

[@tk36_real]

like half the series went straight over my head but I'm still a bit sad it won't keep going looking forward to rewatching it and understanding everything someday (hopefully) - until then I'll watch anything else you cook up

[@A_randomCommenter]

Minor mistake at 06:05 the sign should be a '+' in front of n*log(1-\pi) Besides that, great video, and a wonderful conclusion to the series!

[@-NguyenDuyTanA-mh1db]

he going to explore guys, not gone forever

[@very-normal]

lol yeah I was just tired of saying “very normal therapeutics”, I’ll still be explaining stuff y’all

[@wilderuhl3450]

This video was so good that I forgot my disdain for statistics. Good job.

[@pipertripp]

Class. I just got exposed to the exponential family of distributions in my stat theory class this past semester (start of my masters in applied stats) and suddenly a bunch of things clicked regarding GLMs. This vid was a nice recap of that.

[@tuanminhle8268]

Fantastic!

[@drdca8263]

So, if p_\theta is of that form for both discrete and continuous variables… should I think of this as, “p_\theta is a probability density with respect to some measure, and when it is describing probability, that’s just because it is with respect to the counting measure”? Or, is that not the right way to think about it?

[@very-normal]

Don’t get too lost in the sauce, just think of p_theta as representing a parametric distribution with some parameter vector theta. Once the distribution is specified, it can be talked about with the proper terms. No need to get into measure lol

[@travisleith1146]

Follow up video idea: explain the purpose of the quasi families for GLMs in R

[@AS-hs4xk]

Yooooo Christmas came early this year

[@tkt8994]

Merry Christmas. Please do not stop maykingnvideo or delete any video

[@matthuewalsh1072]

I'm sure this video is very informative, but I though this was about something completely different when I read gay in the thumbnail...

[@junal27]

Well explained, thank you, just subscribed to your channel

[@davidbauerbach8156]

Great video! But since you only cover the basic concepts it would be nice if you could provide some additional resources.

[@very-normal]

Sure! What kind of resource did you have in mind?

[@adekoyasamuel8788]

I think I lack some prerequisites

[@ploutarkhos]

g(EY) matahamtics

[@pfizerpflanze]

Put a like, now I can watch the video

[@Practicalinvestments]

I mean, you don’t have to make things up lol the video is fine without exaggerations. I don’t know what “people” you know that think statistics have always just “existed” but everyone i’ve ever met, correctly; assumes statistics was a human invention, Anyway good video otherwise, fairly informative.

[@watcher8582]

I watched this a few hours ago but only now realize that the caption in my inbox says gEY.

[@zyansheep]

i think u need more clickbaity thumbnails :)