Explaining linear regression

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Explaining basic interpretations to linear regression and how to do a hypothesis test with it
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Опубликовано:

13 окт 2024

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Комментарии : 24

@berjonah110 6 дней назад

The name "Least Squares Regression" comes from the fact that the OLS estimators are the solution to a minimization problem. The objective for this minimization is the sum of the squared error. So minimizing this sum gives the smallest (least) squared error. In fact most of the more advanced ML models are based on an extension of linear regression. Most of these don't have an analytic solution like ordinary least squares, but we can solve for the parameters using gradient descent (or variations).

@MattiasL93 День назад

Really enjoyed this video. Great refresher to watch even if you are already familiar with linear regression

@Unaimend 6 дней назад

💙. Thanks again for your nice videos :) Will you also make one about multiple linear regression? I am particular interested in the necessary preconditions for those models, like, for example homorscedacity. EDIT: I should probably wait with those questions until I finish the video

@memelord4639 6 дней назад

you are in luck, i found the video it’s the one you clicked on!

@Unaimend 6 дней назад

@@memelord4639 Indeeds, a lucky day 😅

@Mystic2122 6 дней назад

GOAT yt channel

@AtticusRex-t6g 6 дней назад

This is a great teaching aid for linear regression. One thing though: in your formulation of the normal equations the X is transposed; it should be (X X^T)^{-1} X Y if you're solving X^T \beta = Y.

@johannbauer2863 6 дней назад

7:24 every other relation, that's monotonically increasing: am I a joke to you?

@jaopredoramires 16 часов назад

woops: 6:18 slight typo in treatment (treamtent in the slide) also, love your channel keep up the good work 👏🏼👊🏼

@Eloss69 6 дней назад

Reading about the bases of least squares lately, trying to understand what motivates some researchers to modeling the noise with Gaussian Processes (context of Bayesian Regression). Does anyone has any insight? Nice video coming at the right time !

@KinomaroMakhosini 6 дней назад

Very fun stuff, next Extra sum of squares and coefficients of partial determination?

@Matthew-eb3di 6 дней назад

MY FAVORITE STATS CHANNEL RELEASED A VIDEO ON MY FAVORITE TECHNIQUE

@andrej5027 6 дней назад

Thanks so much !!!!

@briskioO 6 дней назад

Nice lil intro to regression. Got hit with hat matrices in my linear regression class last week and I nearly perished.

@drdca8263 6 дней назад

7:24 : that something is strictly monotonic doesn’t imply that it is linear though… Edit: oh, someone else already commented this

@very-normal 6 дней назад

ngl monotonic was not what I had in mind when I said that line, but I can see why people would think that, my b

@kventinho 5 дней назад

can you explain? does this mean the word "linear" doesn't refer to that at all?

@very-normal 5 дней назад

I didn’t realize that “the more the merrier” could technically also imply other monotonic increasing relationships. To be more correct, I should have said something along the lines of “another step produces the same change in the outcome”

@victorh2056 4 дня назад

@@kventinho Monotonic functions are those which only ever go one direction (up or down in 2D) or go parallel to the horizontal axis. So, you can imagine a regular constant function is monotonic, a linear function as well, but other functions also display such properties like e^x, log(x), x^2 (0;+ inf), sqrt(x) and so on. They were just pointing that out as these functions could better describe a monotonic increase depending on the data at hand.