Essential Statistics, Regression, and Econometrics


  • Gary Smith, Fletcher Jones Professor, Department of Economics, Pomona College, Claremont, CA, USA

Essential Statistics, Regression, and Econometrics provides students with a readable, deep understanding of the key statistical topics they need to understand in an econometrics course. It is innovative in its focus, including real data, pitfalls in data analysis, and modeling issues (including functional forms, causality, and instrumental variables). This book is unusually readable and non-intimidating, with extensive word problems that emphasize intuition and understanding. Exercises range from easy to challenging and the examples are substantial and real, to help the students remember the technique better.
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Essential Statistics, Regression, and Econometrics is for an introductory non-calculus based statistics course offered in business/finance/psychology departments for undergraduate students of any major who take a term course in basic Statistics or a year course in Probability and Statistics.


Book information

  • Published: June 2011
  • ISBN: 978-0-12-382221-5


"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

Table of Contents

Chapter 1.) Data, Data, Data

Chapter 2.) Displaying Data

Chapter 3.) Descriptive Statistics

Chapter 4.) Probability

Chapter 5.) Sampling

Chapter 6.) Estimation

Chapter 7.) Hypothesis Testing

Chapter 8.) Simple Regression

Chapter 9.) The Art of Regression Analysis

Chapter 10.) Multiple Regression

Chapter 11.) Modeling (Optional)