We begin the analyses by comparing the two groups to see if there is a difference between the groups with respect to the outcome variable, number of days spent in the ICU following surgery (variable name in the worksheet is ICU). We will test Ho: 1 - 2 = 0 versus Ha: 1 - M2 # 0. Subscript 1 refers to the population represented by a sample of patients who received experimental treatment. Subscript 2 refers to the population represented by a sample of patients who received conventional treatment. Use Stat>Basic Statistics>2-sample t, choose the option "samples in one column", select column ICU into samples field, and select column group into subscripts field. Do not check "assume equal variances". Click on options, keep the confidence level at 95%, test difference field should have value 0, and the alternative field should be set to "not equal". We are conducting a two-tailed test to see if there are differences between the groups with respect to the duration of stay in the ICU following surgery: Ho: 1 - 12 = 0 versus Ha: 1 - 12 # 0 Click OK and again OK. Use Minitab's output to answer the following questions: 1. How many patients were randomized to the experimental group (group 1)? 2. How many patients were randomized to the conventional group (group 2)? 3. For the test of Ho: M1 - 12 = 0 versus Ha: 1 - 2 0, what is the value of the test statistic? t= 4. Based on the p-value and 0.05 level of significance, what decision is reached? (a) The experimental and conventional treatments produce the same mean number of days in the ICU stay; (b) The experimental and conventional treatments do not produce the same mean number of days in the ICU stay