Comparing effort prediction models for Web design and authoring using boxplots

Software practitioners recognise the importance of realistic estimates of effort to the successful management of software projects, the Web being no exception. Having realistic estimates at an early stage in a project´s life-cycle allow project managers and development organisations to manage resources effectively. Prediction is a necessary part of an effective process, be it authoring, design, testing, or Web development as a whole. The first part of this paper describes a case study evaluation (CSE) where we measured the characteristics of Web applications and the effort involved in designing and authoring those applications. The second half presents two prediction models generated using statistical techniques, namely linear regression and stepwise multiple regression. The prediction power of the models employed is then compared using boxplots of the residuals. The results suggest that stepwise regression gives better predictions than linear regression