xxi
Introduction
e book contains four sections. In the rst section, we present facts about data. In
the second section, we recapitulate metrics. In the third section, we cover basic laws
of probability. In the fourth section, we present special data patterns in the form of
tailed mathematical distributions.
We are addressing development metrics, maintenance metrics, test metrics, and
agile metrics in separate chapters, paying special attention to the specic problems
in each domain. We also cover the construction of key performance indicators from
metrics.
We also present elementary statistics to understand key characteristics of data:
central tendency and dispersion in two separate chapters. e great contribution
from Tukey in creating a ve-point summary of data and the box plot is presented
in the special chapter.
In Chapter 10, we introduce pattern extraction using histogram. ese patterns
are empirical in nature and are priceless in their capability to show reality as it is.
Going forward, these empirical patterns are translated into mathematical patterns
in individual chapters in terms of statistical distributions. Examples are provided in
each chapter to understand and apply these patterns.
Each chapter is illustrated with graphs. Tables are used to present data where
necessary. Equations are well annotated. Box stories are used to present interesting
anecdotes. In particular, brief notes are presented about original inventors of ideas.
Each chapter contains references on key subjects.
Review questions are presented at the end of each chapter for practice. Exercises
are included for readers to try their hands on the concepts and reinforce learning by
doing. Case studies are presented to explain the practical application of the subjects
covered, where possible. e chapters are organized in such a way that they are easy
to reach, understand, and apply. We have given special emphasis to application
instead of derivation of equations.