First perform a 5 (Major) X 2 (Gender) two-way (or factorial) ANOVA, which is described in Chapter 13 in the Field SPSS book. This analysis lets us determine whether there is a main effect for gender, a main effect for major and an interaction effect for gender X major.
To run this analysis, go to Analyze—General Linear Model—Univariate. Enter Math background as your dependent variable and then Major and Gender as the two Fixed Factors. Now click on OPTIONS, and then Click on Gender, Major and Gender * Major to place these variables over and under DISPLAY MEANS FOR. Also click on Display Descriptive Statistics, then click on Continue. This will allow you to see the means and standard deviations for all of the 10 cells of the study (i.e., female psych majors, male psych majors, female pre-med majors, male pre-med majors etc.).
Use p .05 in order to determine statistical significance.
Click OK to run the analysis.
Descriptive Statistics | ||||
Dependent Variable: Mathquiz | ||||
Gender | Major | Mean | Std. Deviation | N |
1 | 1 | 29.87 | 9.598 | 16 |
2 | 30.89 | 9.740 | 9 | |
3 | 28.70 | 10.231 | 10 | |
4 | 28.89 | 10.130 | 9 | |
5 | 34.67 | 9.074 | 3 | |
Total | 29.94 | 9.520 | 47 | |
2 | 1 | 29.11 | 8.162 | 9 |
2 | 31.17 | 7.259 | 12 | |
3 | 19.22 | 8.511 | 9 | |
4 | 25.33 | 13.204 | 3 | |
5 | 35.80 | 5.263 | 5 | |
Total | 28.00 | 9.447 | 38 | |
Total | 1 | 29.60 | 8.940 | 25 |
2 | 31.05 | 8.182 | 21 | |
3 | 24.21 | 10.401 | 19 | |
4 | 28.00 | 10.436 | 12 | |
5 | 35.38 | 6.301 | 8 | |
Total | 29.07 | 9.480 | 85 |
Tests of Between-Subjects Effects | |||||
Dependent Variable: Mathquiz | |||||
Source | Type III Sum of Squares | df | Mean Square | F | Sig. |
Corrected Model | 1329.704a | 9 | 147.745 | 1.782 | .086 |
Intercept | 55385.376 | 1 | 55385.376 | 667.844 | .000 |
Gender | 98.536 | 1 | 98.536 | 1.188 | .279 |
Major | 892.765 | 4 | 223.191 | 2.691 | .037 |
Gender * Major | 313.988 | 4 | 78.497 | .947 | .442 |
Error | 6219.872 | 75 | 82.932 | ||
Total | 79383.000 | 85 | |||
Corrected Total | 7549.576 | 84 | |||
a. R Squared = .176 (Adjusted R Squared = .077) |
b. As you learned from last week’s one-way analysis of variance, when there is a significant difference found with an analysis of variance we need to know which means are different. If the main effect for gender, which only has two levels (female and male), is significant, you only need to look at the means to see which group scored higher. However, if there is a main effect for Major (which has more than two levels), we need to determine which means differ from which, as you did last week. You do this by running the Tukey post hoc test as you did last week. To do this, go back to Analyze—General Linear Model—Univariate—. Click on Post Hoc and push over Major so that it is underneath Post Hoc Tests for .
Click on Tukey—Continue. Then click on OK to run the analysis.
Paste the results for the Post Hoc Tests here (Multiple Comparisons Table). (5 pts)
Multiple Comparisons | ||||||
Dependent Variable: Mathquiz | ||||||
Tukey HSD | ||||||
(I) Major | (J) Major | Mean Difference (I-J) | Std. Error | Sig. | 95% Confidence Interval | |
Lower Bound | Upper Bound | |||||
1 | 2 | -1.45 | 2.696 | .983 | -8.98 | 6.09 |
3 | 5.39 | 2.772 | .303 | -2.36 | 13.14 | |
4 | 1.60 | 3.198 | .987 | -7.34 | 10.54 | |
5 | -5.78 | 3.699 | .527 | -16.12 | 4.57 | |
2 | 1 | 1.45 | 2.696 | .983 | -6.09 | 8.98 |
3 | 6.84 | 2.883 | .135 | -1.22 | 14.90 | |
4 | 3.05 | 3.295 | .886 | -6.16 | 12.26 | |
5 | -4.33 | 3.784 | .783 | -14.90 | 6.25 | |
3 | 1 | -5.39 | 2.772 | .303 | -13.14 | 2.36 |
2 | -6.84 | 2.883 | .135 | -14.90 | 1.22 | |
4 | -3.79 | 3.358 | .791 | -13.18 | 5.60 | |
5 | -11.16* | 3.838 | .037 | -21.89 | -.44 | |
4 | 1 | -1.60 | 3.198 | .987 | -10.54 | 7.34 |
2 | -3.05 | 3.295 | .886 | -12.26 | 6.16 | |
3 | 3.79 | 3.358 | .791 | -5.60 | 13.18 | |
5 | -7.37 | 4.157 | .396 | -18.99 | 4.24 | |
5 | 1 | 5.78 | 3.699 | .527 | -4.57 | 16.12 |
2 | 4.33 | 3.784 | .783 | -6.25 | 14.90 | |
3 | 11.16* | 3.838 | .037 | .44 | 21.89 | |
4 | 7.37 | 4.157 | .396 | -4.24 | 18.99 | |
Based on observed means.
The error term is Mean Square(Error) = 82.932. |
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*. The mean difference is significant at the .05 level. |
1c. Write up the ANOVA results in APA format below. Be sure to include the post hoc test results in your answer. To see an example of how to write up the results, refer to page 539, section 13.8, in the Field book.
Be sure to begin your results with a statement that begins: A 5 (Major) X 2 (gender) ANOVA was used to examine the relationship of ….. to ……… . State whether the main effects of gender and major were significant, and whether the interaction between gender and major was significant. Then state the results of the post-hoc test.
Please note that it is unnecessary to include effect size but you should indicate the Means and Standard Deviations for the groups that differed significantly (16 points total: 4 points for correctly stating the results of each of the two main effects (i.e. 8 points total for main effects), 4 points for correctly reporting the interaction, and 4 points for correctly reporting the post-hoc test.
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