ABSTRACT
Multiple linear regression represents a generalisation, to more than a single explanatory variable, of the simple linear regression procedure described in Chapter 7. It is now that the relationship between a response variable and several explanatory variables becomes of interest. (Note that in many accounts of multiple linear regression, what we term explanatory variables are called independent variables; however, this is a misleading term because the variables are only rarely independent of one another.) The adjective ‘multiple’ indicates that at least two explanatory variables are involved in the modelling exercise. At the onset, it is important to note that the explanatory variables are strictly assumed to be fixed and under the control of the investigator. That is, they are not considered to be random variables; only the response variable is considered to be a random variable.
