Chapter 12: Regression Diagnostics E370, Spring 2016

Assumptions Data Data Accuracy Measurement accuracy Outliers Observations that may dramatically affect the results of a regression Model Linear relationship The dependent variable is related with the independent variables in a linear fashion. Absence of Multicollinearity Independent variables are not highly correlated with each other

Data Check Check range, mean and other descriptive statistics for data accuracy Outliers: Too far of the predicted value--- Standardized residuals’ absolute value higher than 3 Influential outliers: whose exclusion dramatically changed the coefficients.

Absence of Multicollinearity Check pair-wise correlation coefficients Correlation coefficients higher than 0.8 indicate multicollinearity

Assumptions Error Normality Normally distributed error term Errors cancel on average Error centered at 0 Homoscedasticity Errors have a constant variance over the full range of the dependent variable.

Normally Distributed Error Centered around Zero Histogram of residuals

Homoscedasticity Scatter plot of residuals and predicted values of dependent variable