STATISTICAL TECHNIQUES IN SOFTWARE SIX SIGMA AND DESIGN FOR SIX SIGMA (DFSS) - Software Design for Six-Sigma: A Roadmap for Excellence - page 122

CHAPTER 6

STATISTICAL TECHNIQUES IN
SOFTWARE SIX SIGMA AND DESIGN
FOR SIX SIGMA (DFSS) 1

6.1 INTRODUCTION

A working knowledge of statistics is necessary to the understanding of software
Six Sigma and Design for Six Sigma (DFSS). This chapter provides a very basic
review of appropriate terms and statistical methods that are encountered in this
topic. This statistics introductory chapter is beneficial for software development
professionals, including software Six Sigma and DFSS belts, measurement analysts,
quality assurance personnel, process improvement specialists, technical leads, and
managers.
Knowledge of statistical methods for software engineering is becoming increas-
ingly important because of industry trends 2 as well as because of the increasing rigor
adopted in empirical research. The objectives of this chapter are to introduce basic
quantitative and statistical analysis techniques, to demonstrate how some of these
techniques can be employed in software DFSS process, and to describe the relation-
ship of these techniques to commonly accepted software process maturity models
and standards.
Statistical analysis is becoming an increasingly important skill for software engi-
neering practitioners and researchers. This chapter introduces the basic concepts and

1 This chapter barely touches the surface, and we encourage the reader to consult other resources for further
reference.
2 CMMI Development Team, Capability Maturity Model—Integrated, Version 1.1, Software Engineering
Institute, 2001.