Applied Statistics for Software Managers

Product Description 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. From the Back Cover The easy, complete guide to statistical methods for software project management and process improvement.Use statistics to maximize software process qualityGet results without extensive mathematical experienceLearn from detailed case studies how to identify key factors that influence: Project productivityTime to marketDevelopment effort Maintenance costStatistical 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 productivityAssessing and reducing time to marketUnderstanding 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 About 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. Excerpt. © Reprinted by permission. All rights reserved. PrefaceYou've implemented a measurement program and have collected some software metrics data. Great, but do you know how to make the most of this valuable asset Categorical variables such as language, development platform, application type, and tool use can be important factors in explaining the cost, duration, and productivity of your company's software projects. However, analyzing a database containing many non-numerical variables is not a straightforward task.Statistics, like software development, is as much an art as it is a science. Choosing the appropriate statistical methods, selecting the variables to use, creating new variables, removing outliers, picking the best model, detecting confounded variables, choosing baseline categorical variables, and handling influential observations all require that you make many decisions during the data analysis process. Decisions for which there are often no clear rules. What should you do Read on.Using real software project data, this book leads you through all the steps necessary to extract the most value from your data. In Chapter 1, I describe my methodology for analyzing software project data. You do not need to understand statistics to follow the methodology. I simply explain what to do, why I do it, how to do it, and what to watch out for at each step. Common p
Author: Maxwell, Katrina D.

Publisher: Prentice Hall

Binding: Paperback

Language: English

ISBN-10: 0130417890

ISBN-13: 0076092010432