Calculates the Mean Magnitude of Relative Error (MRE), which measures for a given project the difference between actual and estimated effort relative to the actual effort. The mean takes into account the numerical value of every observation in the data distribution, and is sensitive to individual predictions with large MREs.
Published in Chapter:
Web Development Effort Estimation: An Empirical Analysis
Emilia Mendes (The University of Auckland, New Zealand) and Silvia Abrahão (Valencia University of Technology, Spain)
Copyright: © 2008
|Pages: 31
DOI: 10.4018/978-1-59904-847-5.ch002
Abstract
Effort models and effort estimates help project managers allocate resources, control costs and schedule, and improve current practices, leading to projects that are finished on time and within budget. In the context of Web development and maintenance, these issues are also crucial, and very challenging, given that Web projects have short schedules and a highly fluidic scope. Therefore, the objective of this chapter is to introduce the concepts related to Web effort estimation and effort estimation techniques. In addition, this chapter also details and compares, by means of a case study, three effort estimation techniques, chosen for this chapter because they have been to date the ones mostly used for Web effort estimation: Multivariate regression, Case-based reasoning, and Classification and Regression Trees. The case study uses data on industrial Web projects from Spanish Web companies.