Least Squares Estimators - in summary

[@zvezdelinst]

The best video so far in this course. Brief and clear!

[@nadekang8198]

Doing reviews for econometrics and stats for machine learning, this series is awesome! Thanks Dr. Lambert!

[@rafaelsouza7993]

Ben you are saving my graduation!!! Hello from Brazil

[@UNDERTHESH33TS]

Thanks so much for this course! You are fantastic.

[@pbtheunique5014]

A very hearty thank you from india!!

[@yuchunzhou2788]

Thank u so much for the course!! They are really helpful and clear

[@hshayestehmanesh4837]

Thank you for your clean and clear explanation.
Do you have any playlist arranged the videos in order?

[@hugoharada5301]

Thank you from Brazil!!

[@halimjun759]

You are saving my life

[@Luv579]

You're the besttttt!!!!!!!!!!!!!!! thanks a lot!!!

[@dabaobaobao]

Is there any video missed between NO.20 and NO.21? Because you said at the end of NO.20, in the next video you would talk about the conditions under which the LS estimators are relatively good. (P.S Great videos! Thanks so much for doing it!)

[@barovierkevinallybose1040]

For clarification do we divide by the standard deviation (the square root of the variance) or do we divide by the variance as you did?

[@spandanganguli6903]

You mean for Beta, right? It's variance, (X-Mean of X)^2

[@marcelotorres5736]

love u

[@exec9292]

this vid is total nonsense...

[@trouserpython3857]

@exec9292. I think it was presented by your Mom

[@bigfriki]

exec9292 it made perfect sense dude