Essential Statistics, Regression, and Econometrics

Gary Smith (Autor)

Buch | Softcover

400 Seiten

2026 | 3rd edition
Academic Press Inc (Verlag)
978-0-443-44807-2 (ISBN)

Noch nicht erschienen (ca. Juni 2026)
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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.

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.

1. Data, Data, Data
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

Erscheint lt. Verlag	9.6.2026
Verlagsort	San Diego
Sprache	englisch
Maße	191 x 235 mm
Themenwelt	Mathematik / Informatik ► Mathematik
ISBN-10	0-443-44807-8 / 0443448078
ISBN-13	978-0-443-44807-2 / 9780443448072
Zustand	Neuware