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What is the demand equation estimated in this regression? What does the R 2 and adjusted R 2 say abut this regression

What is the demand equation estimated in this regression? What does the R 2 and adjusted R 2 say abut this regression outcome? Is it a good fit? What is the critical value of F? Does the estimated F value indicate significance at the 95% level?

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What is the demand equation estimated in this regression? What does the R 2 and adjusted R 2 say abut this regression

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  1. What is the demand equation estimated in this regression? • What does the R2 and adjusted R2 say abut this regression outcome? Is it a good fit? • What is the critical value of F? Does the estimated F value indicate significance at the 95% level? • Which of the explanatory variables are statistically significant? How do you know? • How many standard deviations from zero is the estimate for income? What does that tell you about the relationship between Q and Y?

  2. Potential Problems in Regression • Multicollinearity • When two or more explanatory variables are correlated. • Makes it difficult to identify individual impact on dependent variable. • Example – ECON 3125 Grade = f(Class, Hours earned). There is a clear positive relationship between class (junior, senior) and hours earned. • Gives artificially high standard errors and low t-statistics.

  3. Potential Problems in Regression • Heteroscedasticity • Occurs when there is a pattern to the error terms (residuals left over after variances are explained). • The unexplained variances should be because of randomness. When there is a pattern, there is no randomness. • Could occur if dataset includes extremes. For example, if dataset of nations includes group of very large and group of very small. • Can overstate standard errors or understate.

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