Scientific Inference: Learning from Data
Cambridge University Press, 2013; $34.99 (paperback).
This is a surprisingly succinct and fast-paced book in the very crowded field of data analysis. The author teaches a course in data analysis for physics students at the University of Leicester, and the book is geared towards students of physical sciences. Starting with very basic concepts (the scientific method and inductive thinking), the journey concludes with statistical significance and Monte Carlo methods. The book relies strongly on the use of the open source statistical package R, and it includes both tutorials in its use and several well-chosen examples as code samples in each chapter. Not surprisingly, the text is heavily mathematical, but it is readable and includes chapter summaries with key concepts and equations. A companion website includes additional data sets and exercises for students. An extensive glossary, a brief index and a list of references are also included.
Review by Bogdan Hoanca, a professor of management information systems at the University of Alaska Anchorage, U.S.A.
The opinions expressed in the book review section are those of the reviewer and do not necessarily reflect those of OPN or OSA.