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Applied Statistics for Software Managers

Applied Statistics for Software Managers


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About the Book

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 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 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. Graphs. Tables. Correlation Analysis. Stepwise Regression Analysis. Numerical Variable Checks. Categorical Variable Checks. Testing the Residuals. Detecting Influential Observations. 2. Case Study: Software Development Productivity. Creation of New Variables. Data Modifications. Identifying Subsets of Categorical Variables. Model Selection. Graphs. Tables. Correlation Analysis. Stepwise Regression Analysis. Numerical Variable Checks. Categorical Variable Checks. Testing the Residuals. Detecting Influential Observations. 3. Case Study: Time to Market. Model Selection. Graphs. Tables. Correlation Analysis. Stepwise Regression Analysis. Numerical Variable Checks. Categorical Variable Checks. Testing the Residuals. Detecting Influential Observations. 4. Case Study: Developing a Software Development Cost Model. Choice of Data. Model Selection. Graphs. Tables. Correlation Analysis. Stepwise Regression Analysis. Numerical Variable Checks. Categorical Variable Checks. Testing the Residuals. Detecting Influential Observations. Common Accuracy Statistics. Boxplots of Estimation Error. Wilcoxon Signed-Rank Test. Accuracy Segmentation. The 95% Confidence Interval. Identifying Subsets of Categorical Variables. Model Selection. Building the Multi-Variable Model. Checking the Models. Measuring Estimation Accuracy. Comparison of 1991 and 1993 Models. Management Implications. 5. Case Study: Software Maintenance Cost Drivers. It's the Results That Matter. Cost Drivers of Annual Corrective Maintenance (by Katrina D. Maxwell and Pekka Forselius). From Data to Knowledge. Variable and Model Selection. Preliminary Analyses. Building the Multi-Variable Model. Checking the Model. Extracting the Equation. Interpreting the Equation. Accuracy of Model Prediction. The Telon Analysis. Further Analyses. Final Comments. 6. What You Need to Know About Statistics. Describing Individual Variables. The Normal Distribution. Overview of Sampling Theory. Other Probability Distributions. Identifying Relationships in the Data. Comparing Two Estimation Models. Final Comments. Appendix A. Raw Software Development Project Data. Appendix B. Validated Software Development Project Data. Appendix C. Validated Software Maintenance Project Data. Index.

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.


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Product Details
  • ISBN-13: 9780130417893
  • Publisher: Pearson Education (US)
  • Publisher Imprint: Prentice Hall
  • Height: 176 mm
  • No of Pages: 352
  • ISBN-10: 0130417890
  • Publisher Date: 26 Jun 2002
  • Binding: Paperback
  • Language: English


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