The general linear model in statistics has the form Y = b0 + b1X1 + b2X2 + ... + bkXk + e, where e
represents a random error term which is assumed to be normally distributed with mean 0 and constant
variance and does not depend on the value of any other observation. A linear regression model is one
example of a GLM. Analysis of variance (ANOVA) and analysis of covariance (ANOCOVA) models are also
examples of GLMs. These use indicator variables to represent the different categorical levels of a factor. An
example of an indicator variable is X1=1 if the subject is male, 0 if female. Then, b1 represents the mean
difference between males and females