Essential Statistics, Regression, and Econometrics - 1st Edition - ISBN: 9780123822215, 9780123822222

Essential Statistics, Regression, and Econometrics

1st Edition

Authors: Gary Smith
eBook ISBN: 9780123822222
Hardcover ISBN: 9780123822215
Imprint: Academic Press
Published Date: 22nd June 2011
Page Count: 394
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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.

Key Features

  • Readable exposition and exceptional exercises/examples that students can relate to
  • Focuses on key methods for econometrics students without including unnecessary topics
  • Covers data analysis not covered in other texts
  • Ideal presentation of material (topic order) for econometrics course


Essential Statistics, Regression, and Econometrics is for an introductory non-calculus based statistics course offered in business/finance/psychology departments for undergraduate students of any major who take a term course in basic Statistics or a year course in Probability and Statistics.

Table of Contents


Chapter 1. Data, Data, Data

1.1 Measurements

1.2 Testing Models

1.3 Making Predictions

1.4 Numerical and Categorical Data

1.5 Cross-Sectional Data

1.6 Time Series Data

1.7 Longitudinal (or Panel) Data

1.8 Index Numbers (Optional)

1.9 Deflated Data

Chapter 2. Displaying Data

2.1 Bar Charts

2.2 Histograms

2.3 Time Series Graphs

2.4 Scatterplots

2.5 Graphs: Good, Bad, and Ugly

Chapter 3. Descriptive Statistics

3.1 Mean

3.2 Median

3.3 Standard Deviation

3.4 Boxplots

3.5 Growth Rates

3.6 Correlation

Chapter 4. Probability

4.1 Describing Uncertainty

4.2 Some Helpful Rules

4.3 Probability Distributions

Chapter 5. Sampling

5.1 Populations and Samples

5.2 The Power of Random Sampling

5.3 A Study of the Break-Even Effect

5.4 Biased Samples

5.5 Observational Data versus Experimental Data

Chapter 6. Estimation

6.1 Estimating the Population Mean

6.2 Sampling Error

6.3 The Sampling Distribution of the Sample Mean

6.4 The t Distribution

6.5 Confidence Intervals Using the t Distribution

Chapter 7. Hypothesis Testing

7.1 Proof by Statistical Contradiction

7.2 The Null Hypothesis

7.3 P Values

7.4 Confidence Intervals

7.5 Matched-Pair Data

7.6 Practical Importance versus Statistical Significance

7.7 Data Grubbing

Chapter 8. Simple Regression

8.1 The Regression Model

8.2 Least Squares Estimation

8.3 Confidence Intervals

8.4 Hypothesis Tests

8.5 R2

8.6 Using Regression Analysis

8.7 Prediction Intervals (Optional)

Chapter 9. The Art of Regression Analysis

9.1 Regression Pitfalls

9.2 Regression Diagnostics (Optional)

Chapter 10. Multiple Regression

10.1 The Multiple Regression Model

10.2 Least Squares Estimation

10.3 Multicollinearity

Chapter 11. Modeling (Optional)

11.1 Causality

11.2 Linear Models

11.3 Polynomial Models

11.4 Power Functions

11.5 Logarithmic Models

11.6 Growth Models

11.7 Autoregressive Models





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About the Author

Gary Smith

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

Affiliations and Expertise

Fletcher Jones Professor, Department of Economics, Pomona College, Claremont, CA, USA


"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