Applied Statistics for Software Managers [Paperback]

Katrina D. Maxwell (Author)

Book Description

ISBN-10: 0130417890 | ISBN-13: 978-0130417893 | Publication Date: June 24, 2002 | Edition: 1

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.

Editorial Reviews

From the Back Cover

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

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.

See all Editorial Reviews

Product Details

• Paperback: 352 pages
• Publisher: Prentice Hall; 1 edition (June 24, 2002)
• Language: English
• ISBN-10: 0130417890
• ISBN-13: 978-0130417893
• Product Dimensions: 9.2 x 6.9 x 0.9 inches
• Shipping Weight: 1.4 pounds (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars  See all reviews (5 customer reviews)
• Amazon Best Sellers Rank: #1,781,478 in Books (See Top 100 in Books)

More About the Author

Discover books, learn about writers, read author blogs, and more.

Customer Reviews

Most Helpful Customer Reviews

8 of 9 people found the following review helpful:

5.0 out of 5 stars Clearly written tutorial and fact book on SW metrics, June 29, 2002

By 

Mike Tarrani "www.tarrani.com" (Deltona, FL USA) - See all my reviews
(COMMUNITY FORUM 04)    (REAL NAME)   

This review is from: Applied Statistics for Software Managers (Paperback)

If you're working in SQA or managing software development projects this book is an excellent introductory text to statistical analysis. Although I found "Measuring the Software Process" by William Florac and Anita Carleton to me a more in-depth book that book assumes that you've established a metrics program and that you already have a working knowledge of statistics.

What I like about this book is that it's a tutorial on the statistical skills and knowledge that you'll need, and it combines this learning goal with the basics of software metrics and how they can be employed to measure productivity, estimate projects, and manage costs and organizational quality. The core approach is data analysis, and the main tools that the book employs are multi-variate techniques, regression analysis and correlation and sensitivity tests. The author has a talent for clearly explaining a dry subject, and while it will take a good deal of effort to master the material because of its nature, the excellent writing and illustrations will make it easy to quickly grasp statistical fundamentals and put them to use.

The lessons are taught within the framework of four case studies that are realistic and apply to the real world. The case study topics are: productivity analysis, analysis of time to market factors, development cost analysis, and maintenance cost drivers. These cover the full range of both internal development and product-line software engineering. I especially like the inclusion of maintenance costs as a topic of study because this area contributes significantly to total costs of ownership, but is often overlooked.

As of the date of this review there are two primary books that address measurement from a statistical perspective: this one and Florac's and Carleton's "Measuring the Software Process". Deciding which is better is a matter of assessing your needs. The key strengths of this book is the tutorial nature and the wide range of case studies that are used to reinforce the learning. The key strengths of "Measuring the Software Process" is that it goes much deeper into analysis and also includes statistical process controls and other techniques that are present in highly mature development organizations. Regardless of which book you choose (or if you choose both), the information and knowledge to be gained is the foundation of SQA and best practices in project management.

3 of 3 people found the following review helpful:

5.0 out of 5 stars A must read for any one interested in s/w metrics & mgmt., October 24, 2002

By 

Sunita Chulani (San Jose, CA USA) - See all my reviews

This review is from: Applied Statistics for Software Managers (Paperback)

Being a researcher in software metrics, I am really pleased to see a book that is suited for software managers with the correct level of detail in statistics. I particularly enjoyed reading the 4 chapters with case studies. Its a must have for anyone in the field of software metrics and measurement.

1 of 1 people found the following review helpful:

5.0 out of 5 stars A Software Metrics Must Have, October 5, 2002

By 

Barb Most (White Bear Lake, MN United States) - See all my reviews

This review is from: Applied Statistics for Software Managers (Paperback)

This book has a powerful format that blends practical "how to" and common sense with the power and rigor of statistical analysis. I will use this book as a "primer" when implementing software metrics in the corporate arena. This book is a "must have" for anyone implementing a corporate software measurement program. I also wish I had this book in my graduate offerings for Software Development and Design. Existing software curriculums can be sadly lacking the foundations and fundamentals for software measurement and statistics. This book literally makes statistics easy, sensible, and straight forward even for the complexities of software development and technology.