题目
多项填空题
Question at position 27 The impact of Greta Thunberg’s documentary “A Year to Change the World” had on older U.S residents' attitudes towards environmental protection policies. Before watching the documentary, 25 participants ages 65-75-years answered a series of questions regarding their views on the implementation of stringent environmental regulations. After completing the questionnaire, they watched the documentary, and then they completed the questionnaire a second time. Scores ranged from 30 to 100, with higher scores indicating more favorable attitudes towards implementing environmental regulations. What kind of statistical test should you run? Printed Blank[input]Question Blank 1 of 6[input] The Printed Blank[input]Question Blank 2 of 6[input] hypothesis is: There is NO difference between population mean attitudes towards environmental regulations before and after watching the documentary. In symbols, the null hypothesis is: Printed Blank[input]Question Blank 3 of 6[input] Instead of having you run through the steps to calculate a t-test by hand, I'll give you the calculated t-test statistic: t = -2.93. Now, find your t-critical value: Printed Blank[input]Question Blank 4 of 6[input]. Should you reject or fail to reject the null? Printed Blank[input]Question Blank 5 of 6[input] In your interpretation, you'd say: We Printed Blank[input]Question Blank 6 of 6[input] enough evidence to reject the null. We can conclude that there is a difference between population mean attitudes towards environmental regulations before and after watching the documentary. independent samples t-test1-sample t-testdependent samples t-testcorrelationz-testalternativenullµ = 30µ ≠ 30µbefore = µafterµbefore ≠ µafter2.0642.0602.0522.056fail to rejectrejectdo not havehave
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思路分析
The question presents a within-subjects design where the same 25 participants completed a questionnaire before and after watching the documentary, and asks which test and corresponding statements fit.
Option A: 'dependent samples t-test' — This is the correct type of test for comparing two related means (pre- and post-test on the same individuals). A paired (dependent) t-test accounts for the relatedness of the measurements and typically yields more power than an independent t-test in this design.
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