1. 1 SOC 3811 Basic Social Statistics

2. 2 Reminder  Hand in your assignment 6  Remember to pick up your previous homework  Hand in the extra credit assignment next Tuesday in lecture (May 1st)  No lab next Friday (May 4th).  Final exam: May 12 th (Saturday), 8:00am

3. 3 Class overview  Extra credit assignment example  Evaluation  Assignment 5 correction  General review  Time for your extra credit assignment

4. 4 Extra credit example  SPSS commands  Data split file organize output by groups group based on : sex  Analyze descriptive statistics crosstabs check “ CHI-square ” & Expected

5. 5 Extra credit example male

6. 6 Extra credit example female

7. 7 Extra credit example male

8. 8  OR (4+ per week v.s not at all)= 30 (4+ weekly, very happy) / 8 (4+ weekly, not happy) 37 (not at all, very happy) / 24 (not al all, not happy) 30 (4+ weekly, very happy) / 37 (not al all, very happy) 8 (4+ weekly, not happy) / 24 (not al all, not happy = 2.43

9. 9 Extra credit example male  For male, men who have more than 4 times sex per week are 2.43 times more likely to be very happy as opposed to not too happy, relative to those who don ’ t have sex. men who have more than 4 times sex per week are 143% more likely to be very happy as opposed to not too happy, relative to those who don ’ t have sex.

10. 10 female

11. 11 Extra credit example female  OR (4+ per week v.s not at all)= 18 (4+ weekly, very happy) / 9 (4+ weekly, not happy) 83 (not at all, very happy) / 78 (not al all, not happy) 18 (4+ weekly, very happy) /83 (not al all, very happy) 9 (4+ weekly, not happy) / 78 (not al all, not happy = 1.88

12. 12 Extra credit example female  For female, women who have more than 4 times sex per week are 1.88 times more likely to be very happy as opposed to not too happy, relative to those who don ’ t have sex. women who have more than 4 times sex per week are 88% more likely to be very happy as opposed to not too happy, relative to those who don ’ t have sex.

13. 13 Extra credit example compare men and women  Take the odds ratio of odds ratios 2.43 1.88 = 1.29  Interpretation?

14. 14 Extra credit example compare men and women  Start your description from the denominator group, then describe how the relationship is stronger (or weaker) for the numerator group  Women who have sex more than 4 times per week are 1.88 times more likely to be very happy as opposed to not too happy, relative to women who don ’ t have sex. For men, the relationship is 1.29 times stronger.

15. 15 Extra credit example compare men and women  Women who have sex more than 4 times per week are 1.88 times more likely to be very happy as opposed to not too happy, relative to women who don ’ t have sex. For men, the relationship is 29% stronger.

16. 16 Evaluation  Yu-Ju Chien Spring 2007  Sociology 3811 Sec 6 (Friday morning) Sec 7 (Friday afternoon)  16. Cultural difference is a problem for working with Yu-Ju.  17. Language is a problem for working with Yu-Ju. 1 2 3 4 5 6 7 strong agree strong disagree  I ’ ll be back in 10 mins

17. 17 Assignment 5  F-test: gate keeper test  T-test: compare means

18. 18 F-test  H o : variances are equal  H a : variances are not equal  If Sig. (p value)>.05 → can ’ t reject H o (variances are equal)  If Sig. (p value)≤.05 → reject H o (variances are not equal)

19. 19 T-test (two-tail) Ho:Ho: H a :  Calculating z/t score: (note: the formula is different for different type of cases)

20. 20 T-test

21. 21 Review  Inferential statistics :  Regression models  T-test + F test  Pearson ’ s Chi-Square test + Odds ratio

22. 22 Review  Inference review  Two steps in inference: 1. Use a sample to develop population estimates. 2. Use inference to see if estimate is significant (Is our estimate far enough away from a predetermined value to be sure that it is different). (Reject the null. )

23. 23 Inference in regression  Regression models: test if the effects of independent variables on dependent variables are statistically significant.

24. 24 Inference in regression  most often we are comparing our estimate to zero.  In regression if the slope is 0, there is no relationship.  In regression if the slope is not 0, there is some relationship. (then, go further to explain the relationship: positive/negative.)

25. 25 Dummy regression model  T-test compare means of two groups (if independent, it is same as a dummy regression model)  gate keeper test: the F test test if the variances are equal

26. 26 Reminder  Hand in your assignment 6  Remember to pick up your previous homework  Hand in the extra credit assignment next Tuesday in lecture (May 1st)  No lab next Friday (May 4th).  Final exam: May 12 th (Saturday), 8:00am