Clinical depression is a recurrent illness requiring treatment and often hospitalization. Nearly 50% of people who have an episode of major depression will have a recurrence within 2-3 years. Being able to prevent the recurrence of depression in people who are at risk for the disease would go a long way to alleviate the pain and suffering of patients. During the 1980's the federal government, through the National Institutes of Health (NIH), sponsored a large clinical trial to evaluate two drugs for depression. There were 3 treatment groups. Patients received either Imipramine (Imip), Lithium (Li), or a Placebo (Pl). Researchers randomly assigned patients to one of the 3 treatment groups and followed them for 2-4 years to track any recurrences of depression. (Prien et al., Archives of General Psychiatry, 1984).Variables Hospt: Which hospital the patient was from: Labeled 1, 2, 3, 5 or 6 Treat: 0=Lithium; 1=Imipramine; 2=Placebo Outcome: 0=Success 1=Failure (recurrence of depression) Time: Number of weeks until a recurrence (if outcome=1) or until study ended (if outcome=0) AcuteT: How long the patient was depressed before the start of the current study, measured in days Age: Age in years Gender: 1=Female 2=MaleDataIf you have not done so already, download the depression datafile (as always, if a login box opens, just close it and then download the file). Then upload the file in StatCrunch. PromptWe will analyze the data to answer the second research question: Which of the drugs (if either) delayed the recurrence of depression longer relative to the placebo? In the previous lab-preparation activity, we identified Treat as the explanatory variable and Time as the response variable. We also determined that we will analyze the data using side-by-side boxplots and descriptive statistics (i.e. 5-number summaries since the graphs are boxplots). Make graphs and tables. Use StatCrunch to produce side-by-side boxplots. (directions) Embed your graphs with your initial post. Use StatCrunch to produce the descriptive statistics (a table containing the 5-number summaries for each comparison group). (directions) Copy and paste the StatCrunch output table into your initial post. Analyze the data: Compare the distributions for the treatment groups as demonstrated in Unit 2. For example, compare medians and intervals of typical values. Describe the shape and any outliers. Be sure to write your comparisons so the reader can understand the context of the numbers. For example, don't just say the median is 30; instead, say something like this: on average patients taking the placebo relapsed in 30 days (Q2=30 days). Draw a conclusion: What can we conclude from your analysis? Did one drug successfully delay a relapse of depression better than the others? What evidence supports your conclusion? Summarize your conclusions in response to both research questions: In this lab you compared three treatments (two drugs and the placebo) using two different variables. In Part 1 you compared whether or not a relapse into depression occurred for each of the two drugs and the placebo. In Part 2 you compared the length of time until the next relapse for the two drugs and the placebo. What can you conclude in light of both analyses? Is one treatment better than the other? How does the data support your conclusion?