What are the Assumptions of Multivariate Regression?
For the results to be valid, certain assumptions must be met: - Linearity: The relationship between the dependent and independent variables should be linear. - Independence: Observations should be independent of each other. - Homoscedasticity: The variance of errors should be constant across all levels of the independent variables. - Normality: The residuals (errors) should be normally distributed.
