Question

An adviser is testing out a new online learning module for a placement test. They wish to test the claim that the new online learning module increased placement scores at a significance level of α = 0.05 . For the context of this problem, μ d = μ A f t e r − μ B e f or e where the first data set represents the after test scores and the second data set represents before test scores. Assume the population is normally distributed. H o : μ d ≤ 0 H a : μ d > 0 You obtain the following paired sample of 17 students that took the placement test before and after the learning module: After Before 36.7 54.9 61.5 58.9 67.2 51.7 87.1 59.2 57.4 58.5 57 63 61.2 56.7 73.3 45.4 60.7 46.1 54.3 68.4 31.3 45.4 76.4 60.1 51.7 48.8 72 46.7 64.3 70.3 66.7 62.2 65.8 50.3 What is the critical value for this test? Round answers to 4 decimal places. critical value = Shade the sampling distribution curve with the correct critical value(s) and shade the critical regions. The arrows can only be dragged to t scores that are accurate to 1 place after the decimal point (these values correspond to the tick marks on the horizontal axis). Select from the drop down menu to shade to the left, to the right, between or left and right of the t-score(s). Shade: . Click and drag the arrows to adjust the values. Normal curveInterval pointer-1.5 What is the test statistic for this sample? Round answers to 4 decimal places. test statistic = The test statistic is... This test statistic leads to a decision to... As such, the final conclusion is that... the claim that the new online learning module increased placement scores.

Answer 1