The table below summarizes baseline characteristics of patients participating in a clinical trial. a) Are there any statistically significant differences in baseline characteristics between treatment groups? Justify your answer. Characteristic Placebo (n = 125) Experimental ( n =125) P Mean (+ Sd. Age 54 + 4.5 53 + 4.9 0.7856 % Female 39% 52% 0.0289 % Less than High School Education 24% 22% 0.0986 % Completing High School 37% 36%   % Completing Some College 39% 42%   Mean (+ Sd. Systolic Blood Pressure 136 + 13.8 134 + 12.4 0.4736 Mean (+ Sd. Total Cholesterol 214 + 24.9 210 + 23.1 0.8954 % Current Smokers 17% 15% 0.5741 % with Diabetes 8% 3% 0.0438

The following table displays descriptive statistics on the participants involved in a clinical trial that evaluates a new compound designed to improve wound healing in trauma patients. The new compound is compared against a placebo. Are any of the characteristics significantly different between groups? Characteristic New Compound Placebo p-value Mean age (years) 45.2 43.1 0.7564 Men (%) 45% 58% 0.215 Mean educational level (years) 12.1 13.2 0.6898 Mean annual income $36,560 $37,470 0.3546 Mean body mass index (BMI) 24.7 25.1 0.0051 Group of answer choices Mean age and Mean educational level Mean annual income Mean body mass index Mean body mass index and Mean age

Refer to the ANOVA table for this regression.  Source SS d.f. MS Regression 1,164,578 5 232,916 Residual 1,500,689 45 33,349 Total 2,665,267 50    (a) State the degrees of freedom for the F test for overall significance.

Consider the following ANOVA table below. Some parts are blank intentionally. The number of observations is 249. Source Model (Regression) Residual (Error) Total The MSE is: SS 1,332 DF MS 921 Round your answer to two decimal places.

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Suppose we want to compare scores (which can take on any value within a specified range) at baseline and at follow-up for a given sample. Using the data in the table below, compute a 95% CI for the mean difference in scores. Subject ID Baseline Follow-Up 1 13 6 2 10 8 3 9 11 4 12 11 5 8 5

Even if a treatment has no effect, it is still possible to obtain an extreme sample mean that is very different from the population mean. Which outcome is likely if this happens?