Normal view
MARC view
A practical guide to using econometrics / A. H. Studenmund, Occidental College ; with the assistance of Bruce Johnson, Centre College.
Publisher: Boston : Pearson, 2017Edition: Seventh EditionDescription: 572 pagesContent type:- text
- unmediated
- volume
- 9781292154091
- 1292154098
- Using econometrics
- HB 139 .S795 2016
Contents:
An overview of regression analysis -- Ordinary least squares -- Learning to use regression analysis -- The classical model -- Hypothesis testing and statistical inference -- Specification: choosing the independent variables -- Specification: choosing a functional form -- Multicollinearity -- Serial correlation -- Heteroskedasticity -- Running your own regression project -- Time-series models -- Dummy dependent variable techniques -- Simultaneous equations -- Forecasting -- Experiment.
| Item type | Current library | Home library | Collection | Shelving location | Call number | Status | Date due | Barcode | |
|---|---|---|---|---|---|---|---|---|---|
Books
|
American University in Dubai | American University in Dubai | Non-fiction | Main Collection | HB 139 .S795 2016 (Browse shelf(Opens below)) | Available | 5189734 |
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| HB 139 .M3813 1980 Statistical methods of econometrics / | HB 139 .S765 2011 Introduction to econometrics / | HB139.S795 2011 Using econometrics : a practical guide / | HB 139 .S795 2016 A practical guide to using econometrics / | HB 141 .B38 2006 An introduction to modern econometrics using Stata / | HB 141 .K53 1974 An introduction to econometric forecasting and forecasting models / | HB 141 .M63 2008 Modelling and evaluating treatment effects in econometrics / |
Revised edition of the author's Using econometrics, 2011.
Includes index.
An overview of regression analysis -- Ordinary least squares -- Learning to use regression analysis -- The classical model -- Hypothesis testing and statistical inference -- Specification: choosing the independent variables -- Specification: choosing a functional form -- Multicollinearity -- Serial correlation -- Heteroskedasticity -- Running your own regression project -- Time-series models -- Dummy dependent variable techniques -- Simultaneous equations -- Forecasting -- Experiment.
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