What would be the answer for the Homogeneity of Variance Assumption? The Normality of the exam scores was assessed with Shapiro-Wilk and Kolmogorov-Smirnov test reh scores for Group 1 (M=.227, SD=.200) which showed no significant deviations for a normal distribution determined by the Kolmogorov-Smirnov test (D (5) = .227, p = .200) and the Shapiro-Wilk test (W (5) = .897, p = .395). For Group 2 the exam scores (M=.331, SD=.076) showed no significant deviations from the distribution indication. The exam scores for Group 2 (M = .331, SD = .076) did not significantly deviate from a normal distribution, as indicated by the Kolmogorov-Smirnov test (D (5) = .331, p = .076) and the Shapiro-Wilk test (W (5) = .838, p = .159)." Based on the provided output, the two main assumptions for the paired-samples t-test are the level of measurement (interval or ratio) and normality. To determine if the assumptions have been met check the results for the tests of normality. In this case, two tests were conducted: the Kolmogorov-Smirnov test and the Shapiro-Wilk test. For the first variable (exams 1), the Kolmogorov-Smirnov test yielded a statistic of .227 with a significance level of .200. The Shapiro-Wilk test yielded a statistic of .897 with a significance level of .395. For the second variable (exams 2), the Kolmogorov-Smirnov test yielded a statistic of .331 with a significance level of .076. The Shapiro-Wilk test yielded a statistic of .838 with a significance level of .159. Based on these results, we can conclude that the assumptions of normality have been met for both variables, as the significance levels are greater than .05 The assumption of independence is relevant when conducting the paired-samples t-test, as it assumes that the observations within each pair are independent of each other. This assumption ensures that the paired differences between the pre-test and post-test scores are not influenced by any external factors or dependencies.