@Nothingimportant1
It was one of the best videos on youtube. That last interpretation is perfect.
@martinalcala5914
Thank you very much for your videos. I've watched the ones regarding the multiple linear regressions and they've solved lots of doubts that I had!
@Nothingimportant1
I have my stats exam tomorrow and plan to learn R fundamentally by watching your videos. You do a great job.
@valaiopwep7990
Hey thanks for the vids they're a lifesaver, im taking econometrics this semester and as someone with not much experience in stats or programming this helps a lot
@neiltalbert7091
Thanks for the info on Cook's D. It's probably useful when sample sizes are relatively small and outliers could be disproportionately influential.
@intesar_taieb
I wish you can make statistics using R series , I found your explanation straightforward and easy to understand , thank you so much
@AlanCheun
you make good videos, i'd just pad the ends of your video with a few seconds just to let us absorb the final statement and anything on the screen that just changed, youtube will prompt an ad or jump to another video before I can pause or see what just changed
@calmseeker5501
helpful videos of all!
@romanvasiura6705
Thank you!
I guess we should correct a little bit this code (rows 18-19)
new_data <- tibble(x1 = new_x1,
x2 = new_x2)
@Mahdi-Abd-Allah
Thanks you so much for explaining
@almaisaks
Multiple linear regression in R
@haraldurkarlsson1147
I know there are multiple ways of writing the multiple regression line but I am still a bit confused. Since you are using the approximation sign then is the y not y hat? Also does not each x_i have its own error that is epsilon_i. Therefore, in your expression should the epsilon subscript not be k?
@mardzj
at 9:27 shouldn't the null hypothesis be that there is no MLR?
@saminrasi
Hi, I really like the points you mention in your lectures, very helpful! a couple of questions 1. looking at ggpairs graph you mentioned y values doesn't seem to be dependent on the value of x1 or x2 , how did you come to this conclusion? 2.have you also covered nonlinear regression in this channel? Thank you!
@buffaloperformanceandanaly1431
Would there be any difference in the code if there is a positive relationship between one variable and a negative relationship with the second variable? I'm looking at athlete exertion, sleep, and fatigue. Thanks!
@yaweli2968
Is there a site where you have all your loaded video lectures in R?
@EquitableEquations