Applied Statistics for Software Managers

Katrina D. Maxwell

  • 出版商: Prentice Hall
  • 出版日期: 2002-06-24
  • 售價: $2,068
  • 貴賓價: 9.5$1,965
  • 語言: 英文
  • 頁數: 352
  • 裝訂: Paperback
  • ISBN: 0130417890
  • ISBN-13: 9780130417893
  • 相關分類: 機率統計學

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商品描述

The easy, complete guide to statistical methods for software project management and process improvement.

  • Use statistics to maximize software process quality
  • Get results without extensive mathematical experience
  • Learn from detailed case studies how to identify key factors that influence:
  • Project productivity
  • Time to market
  • Development effort
  • Maintenance cost

Statistical techniques offer immense value to managers and developers who want to maximize quality and efficiency throughout the entire software lifecycle. Now there's a guide to using statistical techniques to solve specific software productivity, time-to-market, and maintenance problems. Using actual software project data, Katrina D. Maxwell leads you through every step of the statistical analysis, helping you avoid pitfalls and extract all the value your data has to offer.

You don't need a mathematical background! Maxwell presents an easy-to-follow methodology for analyzing software project data—showing you how to answer crucial questions without getting lost in the data! You'll master statistics through four real-world case studies that address the core issues facing every software manager:

  • Evaluating and improving productivity
  • Assessing and reducing time to market
  • Understanding and minimizing development costs
  • Identifying software maintenance cost drivers-and ameliorating them

Along the way, Maxwell clearly explains each core tool of statistical analysis for software management. You won't just understand regression, correlation, ANOVA, and other key techniques, you'll discover exactly how to make the most of them in your projects!

Software Quality Institute Series

Table of Contents

Preface.
1. Data Analysis Methodology.
2. Case Study: Software Development Productivity.
3. Case Study: Time to Market.
4. Case Study: Developing a Software Development Cost Model.
5. Case Study: Software Maintenance Cost Drivers.
6. What You Need to Know About Statistics.
Appendix A. Raw Software Development Project Data.
Appendix B. Validated Software Development Project Data.
Appendix C. Validated Software Maintenance Project Data.
Index.