Applied Statistics for Software Managers is the first complete guide to using statistical techniques to solve specific software development and maintenance problems. You don't need a mathematical background; Katrina Maxwell presents an easy-to-follow methodology and detailed case studies that show you exactly how to assess productivity, time to market, development costs, maintenance cost drivers, and more.
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The easy, complete guide to statistical methods for software project management and process improvement.
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:
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 SeriesAbout the Author:
KATRINA D. MAXWELL, Ph.D., a leading international expert in the area of software development productivity, is currently a Partner at Datamax in Fontainebleau, France, specializing in software metrics research, data analysis, and productivity benchmarking. Dr. Maxwell has taught courses in business math and statistics at several academic institutions. She has published research in IEEE Transactions on Software Engineering, IEEE Software, and Management Science.
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