Evaluating aptness of a regression model

Abstract

The data for 104 software projects is used to develop a linear regression model that uses function points (a measure of software project size) to predict development effort. The data set is particularly interesting in that it violates several of the assumptions required of a linear model; but when the data are transformed, the data set satisfies those assumptions. In addition to graphical techniques for evaluating model aptness, specific tests for normality of the error terms and for slope are demonstrated. The data set makes for an excellent case problem for demonstrating the development and evaluation of a linear regression model. Copyright © 2007 by Laurie H. Rubel all rights reserved.