Customer Reviews

Applied Statistics for Software Managers

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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.

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.

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.

How often have you presented--or been presented with--an extensive table of raw data only to hear the question "what does it all mean and how can we leverage it?"

There is a wealth of useful data hidden within our own raw data. This book presents the statistical methods required to transform these data into useful information, in the form of mathematical equations (e.g. Cost Estimating Relationships).

It is simply one of the most important texts for Decision Support and Knowledge Discovery you can find. This book is an excellent value and is an absolute must-have for Program Managers, Project Managers, and Parametricians.

The book provides a solid approach towards dealing with software development project data. It is also written in an easy to understand style although the subject itself is far from easy.
This should provide software development managers with a well founded handle to get more grip on development efforts.