DWQA QuestionsCategory: QuestionsAssumptions of Linear regression with SAS
blogger rajeev Staff asked 5 months ago

Let us discuss Assumptions of Linear regression. It is very very important question and will always be asked during Interview.
Linearity – the relationships between the predictors and the outcome variable should be linear
Normality & Independency– the errors should be normally distributed – technically normality is necessary only for the t-tests to be valid, estimation of the coefficients only requires that the errors be identically and independently distributed
Homogeneity of variance (homoscedasticity) – the error variance should be constant
Independence – the errors associated with one observation are not correlated with the errors of any other observation
Errors in variables – predictor variables are measured without error
Model specification – the model should be properly specified (including all relevant variables, and excluding irrelevant variables)