The main strengths of the book lie in its focused approach to topics, outstanding work in alerting students to common mistakes and misinterpretations, and the use of a number of interesting real-life data sets and historical events to flesh out the statistical theory with examples. Much of the analysis—and many of the pitfalls of bad statistical work — are illustrated by reference to real-life errors from academics, politicians, pundits, economic advisers, etc., with examples from economics and the social sciences as well as medicine and law. I can wholeheartedly recommend this book as an introductory book for a statistics course taught to early undergraduate economics students. It is clear and well-written and contains a wealth of interesting examples, exercises, and historical anecdotes. The author has done an excellent job in elucidating statistical methods in an econometric context.ccer. — Ben O’Neill, School of Physical, Environmental and Mathematical Sciences, University of New South Walescer 

This book is written focusing on an introductory statistics course aiming to help students in developing the statistical reasoning they need to follow at a later stage a regression analysis or econometrics course. Within its eleven chapters...the emphasis is placed on statistical reasoning, real data, pitfalls in data analysis and modelling issues, as well as on hundreds of extensive examples and real world case studies which demonstrate in an excellent way the power, elegance and beauty of statistical reasoning. — Zentralblatt MATH 2012-1234-62003

This is an introductory statistics textbook intended for use in either a statistics class that precedes a regression class or a one-term class that encompasses statistics and regression analysis. Complaining of the "fire hose pedagogy" of many introductory statistics courses, Smith (Pomona College) has chosen a focused approach that is intended to provide students with an understanding of the statistical reasoning that is needed for regression analysis. He therefore emphasizes statistical reasoning, real data, pitfalls in data analysis, modeling issues, and word problems. — SciTech Book News