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 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..

If you opt to use statistical software, please report exact p values for each statistical test (e.g., p = .026). Otherwise, if 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

s, assume two-tailed hypothesis tests with ? = .05 unless otherwise specified. All parametric analyses must include effect sizes. Any t-tests include 95% confidence intervals. Any analysis that includes an F-test also include an accompanying ANOVA table. Any analysis that includes a correlation also include the variances of the variables and their cross product (SP; covariability). Any analysis that includes linear regression also include all relevant descriptive statistics (i.e., SSResidual, standard error of the residual, regression equation). Any non-parametric analysis include the ranked scores and the sum of ranks (?R).

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Question 5 (7 marks) A pharmaceutical company is interested in examining the efficacy of a new experimental drug to reduce allergic reactions and therefore recruited subjects to participate in a randomized clinical trial. The researchers exposed participants to a benign allergen to elicit allergic reactions. Half of the participants were assigned to an experimental drug treatment condition in which they were administered the new experimental drug (Drug condition), while the remaining half of participants were placed in a placebo condition in which they received a sham pharmacological treatment (Placebo condition). They measured a continuous-valued, composite index of allergic reaction symptomology to examine whether those who received the experimental drug treatment showed a reduction in allergic reaction symptomology (see Table 5 below). Upon preliminary analysis, the researchers discovered that the assumption of homogeneity of variance was violated: Stargest 6.79 Fmax =- = 4.07, Fmaxcrit = 4.04. Ssmallest 1.67 Furthermore, they realized that the dependent variable was not normally distributed, as scores were heavily positively skewed. Given these observations, using a parametric analysis of the mean difference between conditions is not appropriate. What can the researchers conclude about the efficacy of the drug using a non-parametric analysis? Show all relevant descriptive statistics. Table 5. Composite allergic reaction symptomology scores in the Drug and Control conditions. Subject Condition Scores Drug 1.05 Drug 0.70 Drug 2.10 Drug 0.20 Drug 1.91 6 Drug 1.38 Drug 1.05 8 Drug 4.41 9 Drug 0.29 10 Drug 0.02 11 Placebo 5.73 12 Placebo 8.21 13 Placebo 6.70 14 Placebo 1.00 15 Placebo 2.02 16 Placebo 3.33 Placebo 6.19 18 Placebo 8.47 19 Placebo 2.67 20 Placebo 5.92