Student Solutions Manual for Essential Statistics, Regression, and Econometrics by Gary Smith

Student Solutions Manual for Essential Statistics, Regression, and Econometrics

byGary Smith, Gary Smith

Other | June 16, 2011

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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 .

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) s...
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Details & Specs

Title:Student Solutions Manual for Essential Statistics, Regression, and EconometricsFormat:OtherDimensions:90 pages, 1 × 1 × 1 inPublished:June 16, 2011Publisher:Elsevier ScienceLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0124157750

ISBN - 13:9780124157750

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Extra Content

Table of Contents

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. Modeling (optional)