Essential Statistics, Regression, and Econometrics: Edition 3

· Academic Press
Ebook
400
Pages
Eligible

About this ebook

Essential Statistics, Regression, and Econometrics, Third Edition will helps students in introductory statistics courses develop statistical reasoning and critical thinking skills. The book demonstrates the power, elegance, and beauty of statistical reasoning, providing hundreds of new and updated examples and discussing the uses and potential abuses of statistics. Examples are drawn from real, contemporary areas to showcase that statistical reasoning is not an irrelevant abstraction, but instead an important part of everyday life. This updated resource highlights recent, exciting discoveries and provides a thorough foundation for students, instructors, and researchers alike, all of which are approaching the field from different backgrounds.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
Essential Statistics, Regression, and Econometrics, Third Edition will helps students in introductory statistics courses develop statistical reasoning and critical thinking skills. The book demonstrates the power, elegance, and beauty of statistical reasoning, providing hundreds of new and update...

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About the author

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.
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 ...

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