Multiple regression analysis - Linearity/homoscedasticity

#1
Hello,

I am currently having trouble determining if my predictors show enough linearity to be used in a standard multiple regression analysis, and if I fulfill the requirement of homoscedasticity. Trying to work through a guide on statistics.laerd.com. Would greatly appreciate your feedback

Scatterplots for my six predictors:
predictor 1:


predictor 2:


predictor 3:


predictor 4:


predictor 5:


predictor 6:


Scatterplot over studentized residuals against unstandardized predicted values (homoscedasticity):
 
#2
Multiple linear regression analysis - trying to determine linearity/homoscedasticity

Hi, apologies if this is a double post, I am not sure if my previous went through.

I am trying to write a bachelor thesis and have collected quantitative data with a questionnaire. What I'm trying to do is running a multiple regression analysis to investigate the effect of 6 continous predictors on one continous dependent variable.

I have tried researching by signing up to leard.com and watching videos online, but I have a very hard time determining if my predictors show enough linearity to be used in multiple linear regression, it seems there is only visual inspection to determine this? The same goes for the requirement of homoscedasticity.

I am attaching my six scatterplots for my predictors against the dependent variable, as well as a scatterplot for studentized residuals against unstandardized predicted values trying to determine homoscedasticity.

If I could please have your input based on your visual inspection of these scatterplots if my data fulfills the requirements of linearity and homoscedasticity, and if there are any tests I can actually use besides visual inspection of the scatterplots.

Predictors 1-3:



Predictors 4-6:


Scatterplot studentized residuals against unstandardized predicted values trying to determine homoscedasticity:

Greatly appreciate your input and help, thank you!
Best regards
Alex