Simple Linear and Multiple Regression in SPSS - In Depth 

great video; good pacing; good graphics; clear explanations; thanks!

Awesome! Just to the point. none could explain better than this.

One of the most useful videos ever made on this subject.

This video has been a life saver! The pacing and explanation were so clear, and much easier to understand than most. Thank you so much!

This vide is transparent, crystal clear for regression analysis.

thankyou for being the only helpful video i could find in 2 days!

Great video, very easy to follow!

so very very clear and nice lecture about this subject, so nice speaking ...thanks

Great Video

This is perfect and I have learnt from it thank you ma. But please I would like a video on starting from scratch (data entry) that led to running the regression

You have explained this so well, thank you. However if the assumptions have been violated what is done?

thank you sooo much!

Great and helpful. Thanks

v gud explanation ❤💐

Thank you! I have one question on my analysis Igot beta valuev 0.026 which is positive but sig value is 0.672 which is above 0.05 . should i accept the hypothesis ? Or what can i do?

Thank you so much

Go on

What to do if each variable has dimensions?

Can you please let me know how to correct the autocorrelation? the Value of Durbin Watson test is coming out as .617 How to take it around 2?

Please help me with this issue, i have run bivariate correlation and linear regression. the thing is that, correlation analysis shows positive relationship while regression unstandardized coefficients shows negative, how? is it due to multicollinearity or else....?

6:14 For the coefficient interpretation

Thanks for sharing , May you please add the interpretation as you’re writing in Word.

this is good

thnaks

what to do if the data violates these assumptions?

Can anyone guide me about what to do if the residuals are not normally distributed?

Is problem if Interpreting with out hyphotesis

as the assumption of homoscedasticity is violated , what to do now?

what if you get .000 in the unstandardized B coefficient, but it is statistically significant?

But how do you assess the linearity assumption?😩😭😭

Very informative video sir. If correlation coefficient is positive but regression coefficient (multiple regression analysis) of the variable comes negative what inference can be drawn from such analysis? Kindly tell.

how can i contact you

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