1. Review. POL 242 – 2008-09

2. Strong Correlation. Positive or Negative?

3. Correlations - Views

4. Adding a 3 rd (& 4 th & 5 th ) Variable More than one independent variable. How can we characterize the relationship between these independent variables and the dependent variable.  Additive  Antecedent  Intervening

5. Original Relationship Can Change Did the relationship between X and Y change at different levels of the new variable?  Did the relationship get weaker? stronger?  Did the sign change or stay the same? Focus on the relationship between X & Y, not on how the new variable affects the independent variable.

6. Control Tables Look at a bivariate relationship at different levels of the [new] control variable. Observe appropriate measures of association How can you gauge if there is elaboration?

7. What to do if there is elaboration If the relationship between x and y dramatically changes at different values of z, then you want to create an interaction term. Need a new line with a different slope for those values of z. Remember to include the original variables in the equation as independent variables.

8. Interpreting Interactions Two Dummies  EX: Immigrant and univ graduate. Three coefficients  Immigrant  Univ Graduate  Immigrant * Univ Graduate (Interaction) Immigrant= immigrants w/o univ. diploma Univ Grad = non-immigrant graduates Interaction = immigrants WITH diploma

9. Interpreting Interactions - II Dummy + Ordinal, Ex: Race (white = 1) and Political Interest (ordinal 5 pt scale) Three coefficients  White = effect of being white with no political interest on DV  Political Interest = effect of political interest on DV for non-whites only  Interaction = Effect of political interest on DV for whites only.

10. Regression – To Do Need to run a regression Interpret that regression  B!  Significance Could there be a multicollinearity problem?  Tolerance / VIF  Beta  R-squared

11. Advanced Regression - To Do Recode variables  Create a dummy variable Rules of creating dummies Interpretation of dummies  Create an interaction term Interpretation of all terms in equation Run a regression on sub-sets of sample

12. When should you not run a Regression OLS = Ordinary Least Squares Regression Best for interval dependent variables or ordinal variables with at least five different categories.  Also imposes other restrictions about distribution of variable and the error term You can run a logit regression on a dichotomous dependent variable.

13. Logit Rules You can run a logit regression on a dichotomous dependent variable.  But you cannot directly interpret the coefficients.  You can tell whether the effect is negative or positive, and whether the effect is statistically significant. Remember how to see if the model did a good job of predicting the actual results.

14. Final Product Evaluate your hypothesis or hypotheses.  If evidence is consistent with your hypothesis, reject your null hypothesis. Make your point(s) very clearly. Do your readers know everything they need to know?  And remember that they may not be interested in EVERYTHING.

15. Details Everyone come to class next week (12:15 papers to the office will be marked LATE).  If you are not taking test in-class, you should be in location with internet access. Everyone should fill out an evaluation form.  TAs  Professors Papers go to Turnitin.com

16. Details – Open Book Section Start on internet with Webstats. Can reference class materials (labs, lectures), but your time is limited. May not converse with others (talk, IM, etc) or consult other people’s analyses. Can bring disk or USB memory key to save Word document for your answers (can also save to My Documents) At end, email answers YOURSELF and to pol242y@canada.com and upload to Blackboard. pol242y@canada.com

17. Second Half – Closed Book 28 questions (1/2 value of test) is closed book. NO INTERNET. Multiple choice, true/false, fill in the blank and some short answers. Recommended: 45 minutes Difficulty: should be similar to labs and worksheets.  If you are well-prepared, I expect you will do well.