This assignment lets you explore a quantitative research model using a non-parametric data analytical approach under distribution-free circumstances. By doing this data analysis assignment, you will better understand the concepts, assumptions, requirements, and limitations of binary logistic regression. You will also interpret the results of a non-parametric analysis.

1. For the group of patients that had the low-dose aspirin regimen, calculate the odds of heart attack.
2. For the group of patients that received placebo, calculate the odds of heart attack.
3. Compute the odds ratio that tells us how much more likely a heart attack was for patients in the placebo group (compared with the aspirin group).
4. Compute the odds ratio that tells us how much less likely a heart attack was for patients in the aspirin group (compared with the placebo group).
5. In simple language, how did the aspirin regimen change the odds of heart attack?
6. Now look at the data in a different way. What percentage of the aspirin regimen group had a heart attack? What percentage of the placebo group had a heart attack? Does looking at these two percentages give you a different impression about the impact of aspirin?
7. Describe two different statistical analyses that you could apply to these data to assess whether heart attack is significantly related to drug regimen. (Hint: for a 2 x 2 table, simpler analyses were described in earlier chapters.)

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Solution: The downloadable solution consists of 2 pages, 376 words.
Deliverable: Word Document