Multiple Regression - Interpretation (3of3)

This video presents a summary of multiple regression analysis and explains how to interpret a regression output and perform a simple forecast.

[odaialzrigat]

Thanks Dr. Pat Obi, unbelievably clear explanation, don't know why others over complicate these concepts!

[amantekle]

Watching this lecture is much better than attending my actual lectures online. Thank you!

[aishakendrick]

Thank you for breaking this down. I feel like partial cost of my PhD program should be paid to Youtube (that's bad I know).

[herodmoonga]

Yeah am grateful for your presentation, will fail no exam on this topic, thanks once more Sir, you are indeed a genius

[mukailarafiu]

This presentation is phenominal. May God bless you, sir.

[hendrika]

Seriously, these explanations are so clear and simply brilliant! Thank you so much!

[andreatragni]

You are a wonderful and intelligent human being. Thank you

[toseefdin]

Oh My - so nice to see this video- you were in the strathmore uni orientation day...i am happy to see you here professor

[itismitabiswal]

Thank you so much simple explanation..that no body can give..

[kerrisonmarange]

Honestly i have been helped...thank you for providing such great clarity on the topic.#preps for my next month exams

[iamnotCorinne]

You, Sir, are a lifesaver. Thank you so much!

[SandeepKumar-sgou]

To estimate the Marginal Value Product (MVP) and Marginal factor cost (MFC) equated to allocative efficiency ratio or from regression coefficient of the variables

[Guilopes]

Probably the best clear yet more in depth explanation on the interpretation. So good!
Do you normalize data before the regression? Does it matter? Thanks

[markosmanaye]

Very helpful presentation. Thankyou sir!

[evelynfurtado]

If i have a model where the p value as a whole is not significant, but one independent variable is significant, can it still be reported?

[laar]

thank you so much for the thorough explanation!

[RonanJoyce]

i am doing a question comparing 2 models which each have 3 independent variables. Can i use the fact that Model 2 has a lower standard error of the estimate than Model 1 as a predictor of the dependent variable?.. since this would mean narrow the width of the confidence interval and therefore give smaller margin of error in my prediction of the dependent variable?
Thanks

[collinsagayi]

Wow. Thanks a lot. Now I can interpret my data very well

[malloryalvacastaneda]

Hello Sir, where did you get the number x1=52 and x2=17? maybe i have missed it on your presentation. thank you

[brendanyarko]

what do i do if my r square is less 10% but the model is significant?