Final Comments
Now that you've learned the basics of my methodology for analyzing software project data, you are ready to attack some more complicated databases. In the following four case studies (Chapters 2-5), you will learn how to deal with common problems that occur when analyzing software project data (see Table 1.3). You will also learn how to interpret data analysis results and turn them into management implications.
Table 1.3 Common Problems and Where to Learn How to Deal with Them
|
Chapter 2 Productivity |
Chapter 3 Time to Market |
Chapter 4 Development Cost |
Chapter 5 Maintenance Cost |
Detecting invalid data |
X |
|
|
|
Transforming data before use |
X |
|
|
X |
Categories with too few observations |
X |
|
X |
X |
Outliers |
X |
|
|
|
Choice of best model not obvious |
|
X |
X |
X |
Relationships that don't make sense |
X |
X |
X |
|
Confounded categorical variables |
|
|
|
X |
Choosing baseline categorical variables |
|
|
|
X |
Influential observations |
X |
X |
X |
X |