For these questions, you are given brief summaries of research scenarios, specific hypotheses, and accompanying data. You are required to conduct appropriate statistical analyses of the data to draw conclusions for each research hypothesis. Write a brief report of the results in which you ? Highlight all inferential statistical effects (e.g., There was a strong main effect of Factor A) ? Discuss the qualitative nature of any such effects (e.g., Group A scored higher on than group B) ? Report the results of your statistical tests using the appropriate APA formatting for each respective statistical test (e.g., t[12] = 2.53, p = .026, d = 0.74, 95% CI = [1.34, 4.78]) ? Refer back to the research scenario to make a broad declarative statement about how well the research hypothesis is supported

For all analyses, assume two-tailed hypothesis tests with ? = .05 unless otherwise specified. All parametric analyses must include effect sizes. Any t-tests must include 95% confidence intervals. Any analysis that includes an F-test must also include an accompanying ANOVA table. Any analysis that includes a correlation must also include the variances of the variables and their cross product (SP; covariability). Any analysis that includes linear regression must also include all relevant descriptive statistics (i.e., SSResidual, standard error of the residual, regression equation). Any non-parametric analysis must include the ranked scores and the sum of ranks (?R). You are free to use statistical software (e.g., SPSS, SAS, R, sciPy, MATLAB) to conduct statistical analyses and construct data plots. However, you must provide screenshots of your output as part of your submission. Please embed these images in the word-processed document, rather than submitting them separately. If you would prefer to comput statistical tests and construct data plots by hand on paper, please take photos of your work and embed them into your submission in much the same manner. Alternatively, you could type out your hand calculations, but this would likely be rather tedious and we therefore advise against it.

If you opt to use statistical software, please report exact p values for each statistical test (e.g., p = .026). Otherwise, if you perform hand calculations, report p values in relation to (e.g., less than) the appropriate ?-level (e.g., ? = .05) and include the critical values from the relevant statistical tables provided in the textbook for each statistical test (e.g., p Question 2 A marketing team wants to determine which of two prospective product lines consumers might prefer. They randomly select subjects to participate in a quantitative focus group in which half of the participants were given product A, while the other half of participants were given product B. Participants completed a questionnaire that probed their affinity for the product they inspected during the focus group. Questionnaires items were collapsed into a continuous-valued composite index of product affinity. In a preliminary analysis, the marketing team ensured that the assumption of homogeneity of variance was met: ???? = ???????? 2 ????????? 2 = 5.59 4.33 = 1.29, ????.???? = 4.04 . Given the product affinity data they collected (see Table 2 below), which product are consumers more likely to prefer? Show all relevant descriptive statistics.

Table 2. Product affinity scores for Product A and product B. Subject Product Scores 3.27 2.52 A 4.59 3.84 3.35 7100 A 1.19 A -1.32 11 2.69 12 4104 13 3.26 14 -2108 15 -0.4 16 17 2.97 18 4.17 19 030 20 2.80