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SOC 3811 Basic Social Statistics

SOC 3811 Basic Social Statistics. 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. Class overview.

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SOC 3811 Basic Social Statistics

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  1. SOC 3811 Basic Social Statistics

  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 12th (Saturday), 8:00am

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

  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. Extra credit examplemale

  6. Extra credit examplefemale

  7. Extra credit examplemale

  8. Extra credit examplemale • 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. Extra credit examplemale • 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. female

  11. Extra credit examplefemale • 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. Extra credit examplefemale • 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. Extra credit examplecompare men and women • Take the odds ratio of odds ratios 2.43 1.88 = 1.29 • Interpretation?

  14. Extra credit examplecompare men and women • Start your description from the denominator group, then describe how the relationship is stronger (or weaker) for the numerator group • Womenwho 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. Extra credit examplecompare men and women • Womenwho 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. 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. Assignment 5 • F-test: gate keeper test • T-test: compare means

  18. F-test • Ho: variances are equal • Ha: variances are not equal • If Sig. (p value)>.05 → can’t reject Ho (variances are equal) • If Sig. (p value)≤.05 → reject Ho (variances are not equal)

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

  20. T-test

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

  22. Review • Inference review • Two steps in inference: • Use a sample to develop population estimates. • 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. Inference in regression • Regression models: test if the effects of independent variables on dependent variables are statistically significant.

  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. 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. 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 12th (Saturday), 8:00am

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