Evaluating Significance of Findings Critically evaluate these two scenarios based upon the following points: 1.Critically evaluate the sample size for both scenarios 2.Critically evaluate the statements for meaningfulness for both scenarios 3.Critically evaluate the statements for statistical significance for both scenarios 4.Based on the evaluation, provide an explanation of the implications for social change for both scenarios Scenario 1 A results report that does not find any effect and also has small sample size (possibly no effect detected due to lack of power). A one-way analysis of variance was used to test whether a relationship exists between educational attainment and race. The dependent variable of education was measured as number of years of education completed. The race factor had three attributes of European American (n = 36), African American (n = 23) and Hispanic (n = 18). Descriptive statistics indicate that on average, European Americans have higher levels of education (M = 16.4, SD = 4.6), with African Americans slightly trailing (M = 15.5, SD = 6.8) and Hispanics having on average lower levels of educational attainment (M = 13.3, SD = 6.1). The ANOVA was not significant F (2,74) = 1.789, p = .175, indicating there are no differences in educational attainment across these three races in the population. The results of this study are significant because they shed light on the current social conversation about inequality. Scenario 2 A study has results that seem fine, but there is no clear association to social change. What is missing? A correlation test was conducted to determine whether a relationship exists between level of income and job satisfaction. The sample consisted of 432 employees equally represented across public, private, and non-profit sectors. The results of the test demonstrate a strong positive correlation between the two variables, r =.87, p < .01, showing that as level of income increases, job satisfaction increases as well.