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THE NATURE AND SCOPE OF ECONOMETRICS
BASICS OF PROBABILITY AND STATISTICS
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assume assumption autocorrelation average Chapter CLRM collinearity computed confidence interval constant consumption expenditure correlation covariance data given demand function dependent variable discussed dummy variable Durbin-Watson Econometrics Equation error term example expected value explanatory variables F distribution F test F value following regression given in Eq given in Table heteroscedasticity homoscedastic hypothesis testing import expenditure income lagged least squares level of significance linear regression linear regression model log-linear log-linear model logit mean value multicollinearity multiple regression negative normal distribution Note null hypothesis observations OLS estimators P/E ratio parameters percent probability distribution probability of obtaining problem quantity demanded R2 values random sample random variables regres regression coefficient regression line regression results reject the null relationship residuals sample mean shown in Figure shows specification error standard errors statistically significant sum of squares transformation true type I error var(X widget X2 and X3 zero
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Multilevel Analysis for Applied Research: It's Just Regression!
No preview available - 2007