Using Econometrics: A Practical GuideThis revolutionary text covers single-equation linear regression analysis in an easy-to-understand format that emphasizes real-world examples and exercises. This intuitive approach focuses on learning how to use econometrics, not on matrix algebra or calculus proofs. Clear, accessible writing and numerous exercises provide students with a solid understanding of applied econometrics. This new approach is accessible to beginning econometrics students as well as experienced practitioners. *NEW! A completely new elementary statistics chapter, written by leading statistics author Gary Smith. *NEW! An increased emphasis on modern regression topics like the White test, heteroskedasticity-corrected standard errors, the AR (I) adjustment for serial correlation, Akaike's Information Criterion, the Schwarz criterion, and nonstationarity. *NEW! Improved, expanded, and updated examples, exercises, and data sets. *NEW! Optional, low-cost inclusion of Student Version of EViews, the number-one Windows-based econometric software package in the world, plus a free Student Guide to Using EViews that walks students step-by-step through the EViews software using examples from the main text. *NEW! A Web |
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Contents
An Overview of Regression Analysis | 5 |
4 | 19 |
Ordinary Least Squares | 34 |
Copyright | |
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Common terms and phrases
2SLS answer B₁ calculate chapter Classical Assumption coeffi coefficient estimates constant term critical t-value D₁ data set degrees of freedom dependent disposable income dummy variable dummy variable equal Durbin-Watson econometric econometricians economic equa equation go esti estimated coefficients estimated equation estimated regression example expected value explanatory variables F-statistic Figure forecast functional form go to run heteroskedasticity Hint impact included increase independent variables ith student Least Squares level of significance linear logit mean measure multicollinearity normally distributed null hypothesis observations OLS estimates omitted variable overall fit Park test percent level population PREP regression analysis regression coefficients regression equation regression model regression run reject the null researcher residuals Schwarz criterion Section serial correlation simple correlation coefficient slope coefficients specification standard deviation standard errors statistical t-scores t-Statistic t-test technique theoretical theory tion two-sided Type I Error unbiased variance Woody's X₁ Y₁ zero
References to this book
Discovering Statistics Using SPSS for Windows: Advanced Techniques for the ... Andy P. Field No preview available - 2000 |
Discovering Statistics Using SPSS: (and Sex, Drugs and Rock 'n' Roll) Andy P. Field No preview available - 2005 |