Levenes Test of Equality of Error Variances a Dependent Variable Test

# Levenes test of equality of error variances a

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Levene's Test of Equality of Error Variances a Dependent Variable: Test Performance F df1 df2 Sig. 1.226 5 114 .302 Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a. Design: Intercept + Drug + Alertness + Drug * Alertness

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The assumption of normality of the data on test performance is met. This is seen from the non-statistical significance (p > 0.05) of both Kolmogorov-Smirnova’s Test and Shapiro-Wilk’s Test of Equality of normality. Tests of Normality Kolmogorov-Smirnov a Shapiro-Wilk Statistic df Sig. Statistic df Sig. Test Performance .064 120 .200 * .986 120 .279 *. This is a lower bound of the true significance. a. Lilliefors Significance Correction YOU DID NOT PERFORM TEST OF Homogeneity of variances (-4) Alertness Drug Treatment

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4. Conduct two-way ANOVA with interaction and post hoc analysis (as appropriate) using Tukey to correct for multiple comparisons. Provide relevant SPSS output. (6 points) Tests of Between-Subjects Effects Dependent Variable: Test Performance Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Corrected Model 2066.375 a 5 413.275 12.913 .000 .362 Intercept 44352.075 1 44352.075 1385.793 .000 .924 Drug 363.650 2 181.825 5.681 .004 .091 Alertness 310.408 1 310.408 9.699 .002 .078 Drug * Alertness 1392.317 2 696.158 21.752 .000 .276 Error 3648.550 114 32.005 Total 50067.000 120 Corrected Total 5714.925 119 a. R Squared = .362 (Adjusted R Squared = .334) Multiple Comparisons Dependent Variable: Test Performance (I) Drug Treatment (J) Drug Treatment Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval Lower Bound Upper Bound Placebo Drug A .95 1.265 .734 -2.05 3.95 Drug B -3.13 * 1.265 .039 -6.13 -.12
Tukey HSD Drug A Placebo -.95 1.265 .734 -3.95 2.05 Drug B -4.08 * 1.265 .005 -7.08 -1.07 Drug B Placebo 3.13 * 1.265 .039 .12 6.13 Drug A 4.08 * 1.265 .005 1.07 7.08 Based on observed means. The error term is Mean Square(Error) = 32.005. *. The mean difference is significant at the .05 level. 5. Interpret the analysis results in the context of the research question. Include important statistics from your analysis results to support your conclusion and generalize your results, if appropriate, to the relevant population(s). (5 points) The research question is: Does Drug A or Drug B impair test performance in either fresh or tired test takers? Overall, the drugs have statistically significant effect of the test performance (p < 0.05 in the Tests of Between-Subjects Effects table above). From the multiple comparison table using Tukey HSD, one sees that compared to the placebo group, Drug B has statistically significant (P < 0.05) positive effect in increasing test performances while Drug A is not different from the placebo group to statistically significant level (p = 0.734) in its effect on the test performances. It is also observed that Drug B has statistically significant (p < 0.05) higher effect in increasing the test performances than Drug A.

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II. Multiple Linear Regression (25 points) A health department randomly selected 400 subjects from a local community and monitored their cardiovascular condition. Data from this study are provided in the Final Exam – Linear and Logistic (SPSS document) dataset. The following variables are included in the database: sex, age, BMI, SBP, DBP, serum cholesterol, coronary heart disease, and follow-up.
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