Smith G. Essential Statistics, Regression, and Econometrics

Academic Press, 2012. — 380 p. — ISBN: 0123822211, 9780123822215Essential Statistics, Regression, and Econometrics is for an introductory statistics course with the aim to help students develop the statistical reasoning they need for econometrics. Too many students mistakenly believe that statistics courses are too abstract, mathematical, and tedious to be useful or interesting. To demonstrate the power, elegance, and even beauty of statistical reasoning, this textbook will provide hundreds of interesting and relevant examples, and discuss not only the uses but also the abuses of statistics. These examples will show how statistical reasoning can be used to answer important questions and also to expose the errors-accidental or intentional-that people often make. The examples will be drawn from many areas to show that statistical reasoning is not an irrelevant abstraction, but an important part of everyday life.
This textbook is intended to give students a deep understanding of the statistical reasoning they need for econometrics. It will be innovative in its focus on econometrics, and in the extended emphasis on statistical reasoning, real data, pitfalls in data analysis, and modeling issues (including functional forms, causality, and instrumental variables). This book will be unusually readable and non-intimidating, with extensive word problems that emphasize intuition and understanding.The primary audience is undergraduate students taking a statistics course that is focused on preparing them for an econometrics course. By using this textbook, students will have a good understanding of statistical reasoning, the preparation they need for a subsequent econometrics course, and will have learned the tools for doing research papers involving data analysis.Extensive examples and real world case studies
Tailor-made for economists -teach statistics as a prelude to an econometrics class
A richer introduction to regression analysis
A single resource to help economics students master a difficult subject