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Economics 105: Statistics

Economics 105: Statistics. Go over GH 22 & 23 GH 24 due Monday Individual Oral Presentations … see RAP handout. Dates are Tue April 24 th and Thur April 26 th in lab. But we can’t fit them all into 75 minutes … so extra sessions to be announced.

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Economics 105: Statistics

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  1. Economics 105: Statistics Go over GH 22 & 23 GH 24 due Monday Individual Oral Presentations … see RAP handout. Dates are Tue April 24th and Thur April 26th in lab. But we can’t fit them all into 75 minutes … so extra sessions to be announced.

  2. Dummy Variable Example (with 2 categories) • E[ GPA | EconMajor = 1] = ? • E[ GPA | EconMajor = 0] = ? • Take the difference to interpret EconMajor

  3. Dummy Variable Example (More than 2 categories) • Model the effect of class year on GPA, controlling for study hours

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

  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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