To prepare for this Assignment:<br/> <br/> -Review the Week 5 Scenarios

found in this week’s Learning Resources and select two of the four scenarios for this Assignment. For this Assignment:
Critically evaluate the two scenarios you selected based upon the following points:

-Critically 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.Use proper APA format and citations, and referencing.

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© 2016 Laureate Education, Inc.Page 1 of 2Week 5Scenarios1. The p-value was slightly above conventional threshold, but was described as“rapidly approaching significance” (i.e.,p=.06).An independent samplesttest was used to determine whether student satisfactionlevels in a quantitative reasoning course differed between the traditional classroomand on-line environments. The samples consisted of students in four face-to-faceclasses at a traditional state university (n= 65) and four online classes offered atthe same university (n= 69). Students reported their level of satisfaction on a five-point scale, with higher values indicating higher levels of satisfaction. Since thestudy was exploratory in nature, levels of significance were relaxed to the .10 level.The test was significantt(132) = 1.8,p= .074, wherein students in the face-to-faceclass reported lower levels of satisfaction (M= 3.39,SD= 1.8) than did those in theonline sections (M= 3.89,SD= 1.4). We therefore conclude that on average,students in online quantitative reasoning classes have higher levels of satisfaction.The results of this study are significant because they provide educators withevidence of what medium works better in producing quantitatively knowledgeablepractitioners.2. 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 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 notsignificantF(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.3. Statistical significance is found in a study, but the effect in reality is very small (i.e.,there was a very minor difference in attitude between men and women). Were theresults meaningful?An independent samplesttest was conducted to determine whether differencesexist between men and women on cultural competency scores.The samplesconsisted of 663 women and 650 men taken from a convenience sample of public,private, and non-profit organizations. Each participant was administered aninstrument that measured his or her current levels of cultural competency. The

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© 2016 Laureate Education, Inc.Page 2 of 2cultural competency score ranges from 0 to 10, with higher scores indicating higherlevels of cultural competency. The descriptive statistics indicate women havehigher levels of cultural competency (M= 9.2,SD= 3.2) than men (M= 8.9,SD=2.1). The results were significantt(1311) = 2.0,p<.05, indicating that women aremore culturally competent than are men. These results tell us that gender-specificinterventions targeted toward men may assist in bolstering cultural competency.4. A study has results that seem fine, but there is no clear association to socialchange. What is missing?A correlation test was conducted to determine whether a relationship existsbetween level of income and job satisfaction. The sample consisted of 432employees equally represented across public, private, and non-profit sectors. Theresults of the test demonstrate a strong positive correlation between the twovariables,r =.87,p< .01, showing that as level of income increases, jobsatisfaction increases as well.