Essential Statistics, Regression, and Econometrics
- 3rd Edition - June 9, 2026
- Latest edition
- Author: Gary Smith
- Language: English
Essential Statistics, Regression, and Econometrics, Third Edition will helps students in introductory statistics courses develop statistical reasoning and critical thinking skills… Read more
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 includes extensive word problems that emphasize intuition, understanding, and practical applications.
- Includes hundreds of updated, new, real-world examples that engage students in the meaning and impact of statistics
- Focuses on essential information to enable students to develop their own statistical reasoning
- Provides coverage that is 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
2. Displaying Data
3. Descriptive Statistics
4. Probability
5. Sampling
6. Estimation
7. Hypothesis Testing
8. Simple Regression
9. The Art of Regression Analysis
10. Multiple Regression
11. Replication Crisis
- Edition: 3
- Latest edition
- Published: June 9, 2026
- Language: English
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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.