Statistics and Econometrics
Methods and Applications
1st Edition
Published on 27. May 2002
Book
Hardback
320 pages
978-0-471-10787-3 (ISBN)
Description
Every major econometric method is illustrated by a persuasive, real life example applied to real data.
* Explores subjects such as sample design, which are critical to practical application econometrics.
* Explores subjects such as sample design, which are critical to practical application econometrics.
More details
Edition
1., Auflage
Language
English
Place of publication
New York
United States
Publishing group
John Wiley and Sons Ltd
Target group
College/higher education
Professional and scholarly
Edition type
New edition
Illustrations
illustrations
Dimensions
Height: 24.2 cm
Width: 19.3 cm
Weight
680 gr
ISBN-13
978-0-471-10787-3 (9780471107873)
Schweitzer Classification
Other editions
Previous edition
Orley Ashenfelter | Phillip B. Levine | David J. Zimmerman
Statistics and Econometrics
Methods and Applications. International Edition
Book
03/2003
1st Edition
Wiley
€57.90
Article exhausted; check for reprint
Content
1. Introduction to Econometrics.
2. Basic Probability.
3. Random Variables and Probability Distributions.
4. Mathematics and Expectations.
5. Multivariate Distributions.
6. Sampling and Sampling Distributions.
7. Estimation.
8. Interval Estimation and Hypothesis Testing.
9. Simple Linear Regression.
10. Inference in Simple Linear Regression.
11. Multiple Regression.
12. Extending the Multiple Regression Model.
13. Specification Error, Multicollinearity, and Measurement.
14. Heteroskedascity and Serial Correlation.
15. Simultaneos Equations.
16. Dummy Dependent Variable.
17. Analysis of Time Series Data.
18. Panel Data Models.
2. Basic Probability.
3. Random Variables and Probability Distributions.
4. Mathematics and Expectations.
5. Multivariate Distributions.
6. Sampling and Sampling Distributions.
7. Estimation.
8. Interval Estimation and Hypothesis Testing.
9. Simple Linear Regression.
10. Inference in Simple Linear Regression.
11. Multiple Regression.
12. Extending the Multiple Regression Model.
13. Specification Error, Multicollinearity, and Measurement.
14. Heteroskedascity and Serial Correlation.
15. Simultaneos Equations.
16. Dummy Dependent Variable.
17. Analysis of Time Series Data.
18. Panel Data Models.