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Essentials of econometrics / Damodar Gujarati.

By: Material type: TextTextPublication details: Boston, MA : McGraw-Hill/Irwin, 2006.Edition: 3rd edDescription: xxii, 553 p : ill ; 24 cm + 1 data CD-ROMISBN:
  • 0072970928
  • 0073135941
  • 9780073135946
  • 9780072970920
Report number: 2004058825Subject(s): DDC classification:
  • 330.01'5195 GUJ
LOC classification:
  • HB139 .G85 2006
Contents:
I. The nature and scope of economics II. Basics of probability and statistics III. Characteristics of probability distributions IV. Some important probability distributions 5. Statistical inference: estimation and hypothesis testing 6. Basic ideas of linear regression: the two variable model 7. The two variable model: hypothesis testing 8. Multiple regression: estimation and hypothesis testing 9. Functional forms of regression models 10. Dummy variable regression models 11. Model selection: criteria and tests 12. Multicollinearity: what happens if explanatory variables are correlated? 13. Heteroscedasticity: what happens if the error variance is non constant? 14. Autocorrelation: what happens if Error terms are correlated? 15. Simultaneous equation models 16. Selected topics in single equation regression models
Item type: Books
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Interrnational edition.

Includes index.

I. The nature and scope of economics II. Basics of probability and statistics III. Characteristics of probability distributions IV. Some important probability distributions 5. Statistical inference: estimation and hypothesis testing 6. Basic ideas of linear regression: the two variable model 7. The two variable model: hypothesis testing 8. Multiple regression: estimation and hypothesis testing 9. Functional forms of regression models 10. Dummy variable regression models 11. Model selection: criteria and tests 12. Multicollinearity: what happens if explanatory variables are correlated? 13. Heteroscedasticity: what happens if the error variance is non constant? 14. Autocorrelation: what happens if Error terms are correlated? 15. Simultaneous equation models 16. Selected topics in single equation regression models

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