I am a bit confused with this.
Independence - The response variables are independent. I only have a single response variable so OK? Or observations are independent of each other? E.g Auto Correlated
Normality - The response variable is normally distributed. My response variable (Y) fails a number of normality tests, so not OK. Do I transform to meet this assumption?
Homoscedasticity. - Same variance. Not sure how to test this. Is this part of residual examination? The linear model i am proposing has 4/5 explanatory variables, how do i determine this?
Linearity - Straight line. Well when plotting Y and all X's separately, some are loosely linear. Should I be testing non-linear functions? How do I determine which to use?
I dont have a great deal of time, but I am not comfortable with the current model I am using.
Any help would be great, thank you