Introductory econometrics: intuition, proof, and practice
Introductory Econometrics: Intuition, Proof, and Practice attempts to distill econometrics into a form that preserves its essence, but that is acceptable--and even appealing--to the student's intellectual palate. This book insists on rigor when it is essential, but it emphasizes intuition and seizes upon entertainment wherever possible. Introductory Econometrics is motivated by three beliefs. First, students are, perhaps despite themselves, interested in questions that only econometrics can ans…
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- Full title :Introductory econometrics : intuition, proof, and practice / Jeffrey S. Zax.
Summary
Introductory Econometrics: Intuition, Proof, and Practice attempts to distill econometrics into a form that preserves its essence, but that is acceptable--and even appealing--to the student's intellectual palate. This book insists on rigor when it is essential, but it emphasizes intuition and seizes upon entertainment wherever possible. Introductory Econometrics is motivated by three beliefs. First, students are, perhaps despite themselves, interested in questions that only econometrics can answer. Second, through these answers, they can come to understand, appreciate, and even enjoy the enterpr.
Read More ↓Edition Statements
- Publication Date:©2011.
Publication Statements
- Publisher(s):Stanford Economics and Finance
- Place of Publication:Stanford, Calif
- Language:eng
- Publication Date:©2011.
The Physical Object
- Description:1 online resource (xxvii, 644 pages) : : illustrations
Edition Identifiers
- ISBN:9780804777209, 0804777209
- oclc:ocn722444488
- LC Classification:HB139
- Dewey Decimal:330.01/5195
Table of Contents
Brief Contents; Contents; List of Tables and Figures; Preface; 1. What Is a Regression?; 2. The Essential Tool; 3. Covariance and Correlation; 4. Fitting a Line; 5. From Sample to Population; 6. Confidence Intervals and Hypothesis Tests; 7. Inference in Ordinary Least Squares; 8. What If the Disturbances Have Nonzero Expectations or Different Variances?; 9. What If the Disturbances Are Correlated?; 10. What If the Disturbances and the Explanatory Variables Are Related?; 11. What If There Is More Than One x?; 12. Understanding and Interpreting Regression with Two x's.
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