1. 1 Analysis of Variance ANOVA COMM 420.8 Fall, 2008 Nan Yu

2. 2 Data Collect for your group project On-line questionnaires? Paper questionnaires? What you need to do…

3. 3 Warming Up… Download the following files from ANGEL (folder: week 11).  review practice  review practice answers  ANOVAdata.sav Please complete the questions in “review practice.” Compare your answers to “review practice answers.”

4. 4 T-test Review

5. 5 One-Way ANOVA

6. 6 Analysis of Variance (ANOVA) One-Way ANOVA - ANOVA is used to test differences among more than two groups. - Independent variables must be nominal, more than 2 levels. - Dependent variables must be interval or ratio-level and measured on the same metric.

7. 7 One-Way ANOVA

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9. 9 Assumptions of ANOVA

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12. 12 Hypothesis (ANOVAdata.sav) Attitude toward the ad will vary as a function of the type of ads that are featured on the web site. IV? DV? How many levels (groups) are in the IV?

13. 13 SPSS and ANOVA GSS93 Subset.sav

14. 14 Put the interval or ratio-level variable here. (DV) Put the variable representing the groups here. (IV) Click "Options"

15. 15 Put the group variable in the right window. Then click "continue" and "Ok." Select Compare main effects, Descriptive Statistics, Estimates of effect size, Homogeneity tests, Bonferroni

16. 16 SPSS Output Each group has 20 people

17. 17 Means and standard deviations for each group

18. 18 Homogeneity of Variance is good! Meaning that variances between groups are not significantly different.

19. 19 This is the test statistic. These are degrees of freedom. This is the obtained p-value. F(3, 76) = 21.74, p <.001. Reject the null Effect size

20. 20 This tells you the group of Animated Ad is different than the other three groups. Bonferroni post hoc comparisons.

21. 21 F(3, 76) = 21.74, p <.001, partial η 2 =.46 Interpret One-Way ANOVA with Graphs

22. 22 Interpret One-Way ANOVA with tables The results shows that participants reported significantly more favorable attitudes toward the ad in the animated condition (M = 5.33, SD = 0.92) compared to the text condition (M = 3.59, SD = 0.92), static condition (M = 3.53, SD = 0.68), or the pop-up condition (M = 3.43, SD = 0.93), F (3, 76) = 21.74, p <.001, partial η 2 =.46.

23. 23 Factorial Designs More than one IV, both are nominal, DV is interval or ratio-level Behavioral intention will vary as a function of the type of ads that are featured on the web site and the gender of the participants. IVs? DV?

24. 24 Put the interval or ratio-level variable here. (DV) Put the variables representing the groups here. (IVs) Then Click "Options"

25. 25 Put the group variable in the right window. Then click "continue" and "Ok." Select Compare main effects, Descriptive Statistics, Estimates of effect size, Homogeneity tests.

26. 26 Main Effects Interaction Test statistics Degrees of freedom P-values Significant main effect for Gender, F (1, 72) = 31.55, <. 001, partial η 2 =.31 No significant Main Effect for Condition, F (3, 72) =.74, p =.53, partial η 2 =.03 No significant Gender X Condition interaction, F (3, 72) = 1.19, p =.32, partial η 2 =.05 Effect size

27. 27 Creating Graphs Highlight these two numbers with mouse, right click Create Graph  Bar

28. 28 Significant main effect for Gender, F (1, 72) = 31.55, <. 001, partial η 2 =.31

29. 29 No significant main effect for Condition, F (3, 72) =.74, p =.53, partial η 2 =.03

30. 30 How to Create Line Graphs for Interaction Effects? Double click this table, then right click Select Pivoting Trays

31. 31 Move the small square from bottom to the left Then, the means table will look at this.

32. 32 Highlight these numbers with mouse, then right click Create Graph  Line

33. 33 Graphs for the Interaction Effects No significant Gender X Condition interaction, F (3, 72) = 1.19, p =.32, partial η 2 =.05 These lines are not parallel, we can suspect that there might be interaction effects. But they are not statistically significant.

34. 34 In-class practice (ANOVAdata.sav) Attitude toward the brand will vary as a function of the type of ads that are featured on the web site. -Can we reject the null? -Please report the test statistics and create a bar chart for this result. -Which condition seems to yield least favorable attitude toward the brand?

35. 35 In-class practice Can we reject the null? Yes Please report the test statistics and create a bar chart for this result. F (3, 72) = 31.45, p <.001, partial η 2 =.56 Which condition seems to yield least favorable attitude toward the brand? Text-only