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Scenario 1A 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, pScenario 2A 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 existsbetween educational attainment and race. The dependent variable of educationwas measured as number of years of education completed. The race factor hadthree attributes of European American (n = 36), African American (n = 23) andHispanic (n = 18). Descriptive statistics indicate that on average, EuropeanAmericans have higher levels of education (M = 16.4, SD = 4.6), with AfricanAmericans slightly trailing (M = 15.5, SD = 6.8) and Hispanics having on averagelower levels of educational attainment (M = 13.3, SD = 6.1). The ANOVA was notsignificant F (2,74) = 1.789, p = .175, indicating there are no differences ineducational attainment across these three races in the population. The results ofthis study are significant because they shed light on the current social conversationabout inequality.Assignment for both ScenariosCritically evaluate the sample size.Critically evaluate the statements for meaningfulness.Critically evaluate the statements for statistical significance.Based on your evaluation, provide an explanation of the implications for social change.ResourcesFrankfort-Nachmias, C., & Leon-Guerrero, A. (2015). Social statistics for a diverse society (7th ed.). Thousand Oaks, CA: Sage Publications.Chapter 9, “Testing Hypothesis” (pp. 267-277)Wagner, W. E. (2016). Using IBMÂ® SPSSÂ® statistics for research methods and social science statistics (6th ed.). Thousand Oaks, CA: Sage Publications.Chapter 6, “Testing Hypotheses Using Means and Cross-Tabulation”Warner, R. M. (2012). Applied statistics from bivariate through multivariate techniques (2nd ed.). Thousand Oaks, CA: Sage Publications.Applied Statistics From Bivariate Through Multivariate Techniques, 2nd Edition by Warner, R.M. Copyright 2012 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center.Chapter 3, “Statistical Significance Testing” (pp. 81-124)Applied Statistics From Bivariate Through Multivariate Techniques, 2nd Edition by Warner, R.M. Copyright 2012 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center.Magnusson, K. (n.d.). Welcome to Kristoffer Magnusson’s blog about R, Statistics, Psychology, Open Science, Data Visualization [blog]. Retrieved from http://rpsychologist.com/index.htmlAs you review this web blog, select [Updated] Statistical Power and Significance Testing Visualizationlink, once you select the link, follow the instructions to view the interactive for statistical power. This interactive website will help you to visualize and understand statistical power and significance testing.Note: This is Kristoffer Magnusson’s personal blog and his views may not necessarily reflect the views of Walden University faculty.