The value of R2 varies between 0 and 1; a value of R2 ¼ 0:9 indicates that 90% of the total variability in the response variable is accounted for by the predictor variables. However, a large value of R2 does not necessarily mean that the model fits the data well. Thus, a more detailed analysis is needed to ensure that the model can satisfactorily be used to describe the observed data and predict the response for another set of data different from the one used to generate the model.