1. Firstname lastname aa1111a@american.edu American University School of International Service

2. Power Point Presentation Place – the lab Run the PPT rp.ppt file from your website Duration – 4-5 minutes Number of slides – 6 - 10 Slide 1 – Title Slide 2 – Your Research Question Slide 3 – Background Info\Lit Review Slide 3 - Data Slide 4 – Descriptive Statistics or/and Graphics Slide 5 – Regression Analysis /Contingency Table Slide 6 – Conclusions/Policy Suggestions Paper Discussion – 1 -2 minutes

3. Research Question & Research hypothesis Research Question/s Research hypothesis

4. Background Info or Lit. Review Theory and Findings form paper #1 Theory: Findings : Theory and Findings form paper #1 Theory: Findings :

5. Data Unit of analysis/study : country or individual Source of the data Reliability of the data Dependent variable/s Y is …. Unit of measurement and LOM of Y variable Independent Variable X1 is … Units and LOM of Y variable X2 is.. Units and LOM of Y variable X3 is.. Units and LOM of Y variable

6. Descriptive Statistics Table or/and Graphics What is the central tendency of your dependent/independent variable/s? Provide meaningful explanation of the mean/median (for I-R LOM dependent variable) or the mode (for Nominal or Ordinal LOM variables) Is the distribution of your dependent variable normal uni-modal or is it bi-modal? How credible is the central tendency? What is range of your dependent variables? Do you have missing data?

7. Bivariate analysis - I-R LOM dependent variable Report Correlation table - for I-R LOM dependent variable. Interpretation of reported statistics in these tables: i)Does the association/correlation exists, i.e. is your measure of association/correlation statistically significant? ii) If the association/correlation exists how strong it is? Check the value of the Pearson’s r, gamma or lambda statistic; iii) What is the direction of the association/correlation? Remember that this is for gamma and Pearson’s r statistic, for I_R and ordinal LOM variables only. YX1Research hypothesis X1Pearson’s r=0.25 (0.003), N=1005 Reject the H0. Y and X1 are weakly positively correlated X2Pearson’s r=-0.95 (0.003), N=1005 Pearson’s r=-0.35 (0.003), N=1005 Reject the H0. Y and X2 are strongly negatively correlated

8. Bivariate analysis - Categorical LOM dependent variable. Report Table with Gama/Lambda/Chi square statistic for association of ordinal/nominal data. Report Table with T test/F test statistic for association of ordinal/nominal dependent variable and I-R variables. Interpretation of reported statistics in these tables: i)Does the association/ exists, i.e. is your measure of association/correlation statistically significant? ii) If the association/correlation exists how strong it is? Check the value of the gamma or lambda statistic; iii) What is the direction of the association? Remember that this is for gamma statistic, for I_R and ordinal LOM variables only. Remember that chi square and lambda/gamma statistics may show ambiguous results, i.e. On of the measures suggest associations and the other suggests no association. Y - Gamma:Y – Chi^2:Research hypothesis Z1G=0.25 (0.003), N=1005 χ 2 =125.45 (0.03), N=1005 Reject the H0. Y and X are associated Z2G=0.02 (0.08), N=1005 χ 2 =9.45 (0.045), N=1005 Fail to reject the H0. Y and X are not associated

9. Regression Analysis /Contingency Table 2– The Dependent Variable is …. Model 1Model 2 Model 3 X1 (Sign.) 0.11 (.00) 0.11 (.00) X2 -123.45 (.04) -123.45 (.04) X3.01 (.09 ) N Adj. R^2 189 0.67 189 0.65 Interpretations: i)Does the association, i.e. is your coefficient statistically significant? Look this value. Is it <.05? ii) If the association/correlation exists (sig <.05), what is the direction of the association/correlation, i.e.. What is the sign of the coefficient? iii) interpret the value of each and every statistically significant coefficient. For example, if the dependent and independent variables are not in log-level, and if b1=0.11, we can interpret this coefficients in the following way “one unit change in the independent variable X1 leads to 0.11 units changes in the dependent variables Y.” You can not interpret values of coefficients that are not significant since they are statistical zeros. iv) Make sure you interpret adj. R square statistics.

10. Findings & Policy Implications of the research Findings: Did you accept your research hypothesis? What are the policy implications of your findings?