Researchers conducted a study to test a potential side effect of a new allergy medication. 160 subjects with allergies were used for the study. The new " improved" Brand I medication was randomly assigned to 80 subjects and the current Brand C medication were randomly assigned to the other 80 subjects. 14 of the 80 patients with Brand I reported drowsiness, and 22 of the 80 patients with Brand C reported drowsiness. Is there sufficient evidence to suggest there is a difference between the two brands of allergy medication. The researchers are using alpha 0.05

1. Please write the hypotheses for this problem.

2. Is this a one or two-tailed test? Why?

3. Should you pool the variances? Why or why not?

4. Should you check the random condition? Why or why not?

5. Should you check the 10% condition? Why or why not?

6. Should you check the large counts condition? Why or why not?

7. If you were checking the large counts condition, what would the expected number of successes be for the Brand I group?

8. When do you add standard deviations?

9. If the z-score is-1. 51, what is the p-value? Warning this is a two-tailed test

10. Interpret the p-value in context.

11. What conclusion can you make based on the p-value and the alpha value of 0.05?

12. What type of error (Type 1 vs. Type 2) could you have made? How do you know?

13. What is the probability of making this type of error?

14. What are the consequences of the error above?

15. What is one way you could reduce the probability of the above error?

16. A two-proportion z-interval yields 95% confidence interval of( -0. 2285, 0.0248) . Does this interval support your conclusion in question # 11? Why or why not?