Statistics 101: Multiple Regression, Keeping or Excluding Features 

Thanks for keeping the session alive, I really felt that what you covered in the lecture was something very unique and not alot of educators cover that often. Also, loved that fact that you leave breadcrumbs for cross checking manually like the case of SSE / Df which equals to the value of MSE. These tips and pointers really goes a long in strengthening the concept. Kudos!!

Thank you for making multiple regression more understandable!

Thank you for taking the time to explain the first-principles of statistics. So many classes focus on solving rote equations and moving through the material with needless pressure. Great job.

Love the added, Namaste! Thanks for the great video 🙏

You are so good at teaching that today's my birthday and I am literally begging you to make videos on Ridge, Lasso and Elastic Net regression, Principal Component Regression, Partial Least Square, Spline Regression, Generalized Additive Models, Regression Decision Trees, Regression Random Forests, Bagging and Boosting. Plz don't say that there are other good sources available for them. You are the best. Please I am begging you to make videos on these topics 🙏🏻🙏🏻

Great to see you're back, Brandon! Thanks for the excellent lessons!

It's amazing to see you back Brandon sir. Sir ,it would be very nice of you if you make some videos on sample survey (simple random sampling, cluster sampling, systematic sampling etc.)

Amazing video. You're a life saver. Thanks for all you do for your students.

This is so helpful :) Thank you so much for all your work to make these videos!

Hi, Brandon! Congratulations for your excellent videos, they are very instructive, clear and interesting. I would like to suggest you something: Would it be interesting to compare the method you use in this video to include or exclude Independent Variables, with the things you pointed in the videos 3 and 4 (Evaluating Basic Models). I mean: correlations between Independent Variables and how well or bad every Independent Variable explains the Dependent Variable. For example, I guess that the number of bathrooms is correlated with the number of bedrooms and square feet. Also it would be nice to include another Independent Variable, such the Year of Construction of the houses. I guess that this kind of Variable would be correlated with the number of bedrooms (some years ago flats had more bedrooms and less bathrooms...). Anyway, I'll try to observe this kind of things by myself, as an exercise. Greetings from Spain!

You have no idea how much these videos have helped me and my dissertation! Any chance you could do one on HLM (as an extension of regression)? With gratitude!

This is a wonderful video. I appreciate

Awesome stuff and awesome teacher....

Loved your NAMASTE. Thanks for considering other cultures.

You are back, Sir! Thank you so much! We are exciting about your new videos. Loves from Azerbaijan! :)

Hello Brandon. How do we approach for including/excluding categorical variables? Do we add each category within that variable one by one and test or do we add all of them together and test?

You are awesome.. and i have found that length of a video and its views are inversely correlated..

OMG the Namaste ❤️

Thanks

Hello, there sir! I am really fond of this Multiple Regression Series. May I know what resources/books can I use to study further this type of regression.

Can I get data set for understanding? Where can I download it from?

Great video! Can this technique be used only for simple multiple regression, or would it work with more complex ensemble methods like gradient boosting, too?

Namaste and Thank you for great video....Sir I have a query on Z value calculation and would like to ask it with example.....how can I submit my query to you...... Thanks in advance for your reply.

Brandon, minor observation: is this video 8 of playlist 15? The front page of this video says is number 6 but there’s one already in playlist 15. Please let us know. Thanks for this excellent video!!!!

16:45, the numerator should be SSR (partial), not SSE. And the denominator is full MSE.

we miss you bro

Heteroscedasticity please