For further information on analysis of residuals please see Belsley et al. Standard error for the predicted Y, leverage hi (the ith diagonal element of the hat (XXi) matrix), Studentized residuals, jackknife residuals, Cook's distance and DFIT are also given with the residuals. You might also wish to inspect a normal plot of the residuals and perform a Shapiro-Wilk test to look for evidence of non-normality. It is good practice to examine a scatter plot of the residuals against fitted Y values. The influential data option in StatsDirect gives an analysis of residuals and allows you to save the residuals and their associated statistics to a workbook. If the pattern of residuals changes along the regression line then consider using rank methods or linear regression after an appropriate transformation of your data.
it is the distance of the point from the fitted regression line. blood group) then you should consider splitting it into separate dichotomous variables as described under dummy variables.Ī residual for a Y point is the difference between the observed and fitted value for that point, i.e. If one of the predictors in a regression model classifies observations into more than two classes (e.g.
This is a generalised regression function that fits a linear model of an outcome to one or more predictor variables. Menu location: Analysis_Regression and Correlation_Multiple Linear.