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Economics 105: Statistics

Economics 105: Statistics. GH 24 due Monday. Their variable of interest. Interaction Effect Example. Does the effect of study hours on GPA differ by major?. Interaction effect. Hypothesis Tests on Several Regression Coefficients. Consider the model (expanding on GH 22)

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Economics 105: Statistics

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  1. Economics 105: Statistics GH 24 due Monday

  2. Their variable of interest

  3. Interaction Effect Example • Does the effect of study hours on GPA differ by major?

  4. Interaction effect

  5. Hypothesis Tests on Several Regression Coefficients • Consider the model (expanding on GH 22) • Is “race” as a group significant?

  6. Hypothesis Tests on Several Regression Coefficients

  7. Hypothesis Tests on Several Regression Coefficients • To test • Use F statistic • Impose the restrictions to get “restricted” terms • m is the number of restrictions • Reject H0 if Intuition?

  8. Hypothesis Tests on Several Regression Coefficients

  9. Hypothesis Tests on Several Regression Coefficients

  10. Hypothesis Tests on Several Regression Coefficients

  11. Multiple Regression: Example where Sign Switches Correlations Rating Age Income Rating 1.000 0.587 0.885 Age 0.587 1.000 0.829 Income 0.885 0.829 1.000 Survey of 75 consumers Rating = rating of likelihood of purchase of a PDA (e.g., palm pilot) on a scale of 1-10, 10 indicating highest likelihood. Age = age in years Income = income in thousands of dollars

  12. Multiple Regression: Example where Sign Switches Regression of Rating on Age Estimate Std Error t Ratio Prob>|t| Intercept 2.067 0.487 4.24 <.0001 Age 0.059 0.009 6.19 <.0001 Regression of Rating on Income Term Estimate Std Error t Ratio Prob>|t| Intercept -0.596 0.352 -1.69 0.0951 Income 0.070 0.004 16.20 <.0001

  13. Multiple Regression: Example where Sign Switches Multiple Regression Estimates Term Estimate Std Err t Ratio Prob>|t| Intercept -0.736 0.295 -2.50 0.0149 Age -0.047 0.008 -5.74 <.0001 Income 0.101 0.006 15.63 <.0001 Conclusions?

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