Essential Statistics, Regression, and Econometrics
- 3rd Edition - September 1, 2026
- Latest edition
- Author: Gary Smith
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 4 4 8 0 7 - 2
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 4 4 8 0 8 - 9
Essential Statistics, Regression, and Econometrics, Third Edition, is intended to help students in an introductory statistics course develop their statistical reasoning and… Read more
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Essential Statistics, Regression, and Econometrics, Third Edition, is intended to help students in an introductory statistics course develop their statistical reasoning and critical thinking skills. To demonstrate the power, elegance, and even beauty of statistical reasoning, this book provides hundreds of new and updated examples, and discusses not only the uses but also the abuses of statistics. The examples are drawn from many real, contemporary areas to show that statistical reasoning is not an irrelevant abstraction, but an important part of everyday life. Innovative in its extended emphasis on statistical reasoning, real data, pitfalls in statistical analysis, the perils of p-hacking and data mining, and modeling issues, including functional forms and causality, the book is readable and non-intimidating, with extensive word problems that emphasize intuition, understanding, and practical applications. Now in its Third Edition, this popular resource highlights recent exciting discoveries and provides a thorough foundation for students, instructors, and researchers alike, all approaching the field from a variety of backgrounds.
• Includes hundreds of updated and new, real-world examples to engage students in the meaning and impact of statistics
• Focuses on essential information to enable students to develop their own statistical reasoning
• Provides coverage ideal for one-quarter or one-semester courses taught in the fields of economics, business, finance, politics, sociology, and psychology departments, as well as in law and medical schools
• Offers an ancillary website with an instructors solutions manual, student solutions manual, worked-out exercises, and supplemental chapters
• Focuses on essential information to enable students to develop their own statistical reasoning
• Provides coverage ideal for one-quarter or one-semester courses taught in the fields of economics, business, finance, politics, sociology, and psychology departments, as well as in law and medical schools
• Offers an ancillary website with an instructors solutions manual, student solutions manual, worked-out exercises, and supplemental chapters
Upper-level undergraduate and graduate students majoring in statistics or related fields
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: Replication Crisis Appendix References Index
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: Replication Crisis Appendix References Index
- Edition: 3
- Latest edition
- Published: September 1, 2026
- Language: English
GS
Gary Smith
Gary Smith received his Ph.D. in Economics from Yale University and was an Assistant Professor there for seven years. He has won two teaching awards and written (or co-authored) more than 100 academic papers and 20 books. His Standard Deviations: Flawed Assumptions, Tortured Data, and Other Ways to Lie with Statistics (Overlook/Duckworth, 2015) was a London Times Book of the Week and has been translated into Chinese, Japanese, Korean, and Turkish. The AI Delusion (Oxford University Press, 2018) argues that, in this age of Big Data, the real danger is not that computers are smarter than us, but that we think computers are smarter than us and, so, trust computers to make important decisions they should not be trusted to make. The 9 Pitfalls of Data Science (Oxford University Press, 2019, co-authored with Jay Cordes), won the PROSE award for Excellence in Popular Science & Popular Mathematics. His statistical and financial research has been featured in various media, including The New York Times, Wall Street Journal, Wired, NPR Tech Nation, NBC Bay Area, CNBC, WYNC, WBBR Bloomberg Radio, NBC Think, Silicon Valley Insider, Motley Fool, Scientific American, Forbes, MarketWatch, MoneyCentral.msn, NewsWeek, Fast Company, The Economist, MindMatters, OZY, Slate, and BusinessWeek.
Affiliations and expertise
Fletcher Jones Professor, Department of Economics, Pomona College, Claremont, CA, USA