Essential Statistics, Regression, and Econometrics

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9780123822215: Essential Statistics, Regression, and Econometrics

"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. It offers readable exposition and exceptional exercises/examples that students can relate to. It focuses on key methods for econometrics students without including unnecessary topics. It covers data analysis not covered in other texts. It includes ideal presentation of material (topic order) for econometrics course.

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Review:

"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

About the Author:

Gary Smith received his B.S. in Mathematics from Harvey Mudd College and his PhD in Economics from Yale University. He was an Assistant Professor of Economics at Yale University for seven years. He is currently the Fletcher Jones Professor of Economics at Pomona College. He has won two teaching awards and has written (or co-authored) seventy-five academic papers, eight college textbooks, and two trade books (most recently, Standard Deviations: Flawed Assumptions, Tortured Data, and Other Ways to Lie With Statistics, Overlook/Duckworth, 2014). His research has been featured in various media including the New York Times, Wall Street Journal, Motley Fool, NewsWeek and BusinessWeek. For more information visit www.garysmithn.com.

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