Based on past data, it is known that about 8.96% of people who go to the doctor end up testing positive for influenza. Suppose we take a sample of 100 doctor visits and find that 9.17% of people test positive for influenza. We want to see if there is evidence that the percentage of people who have influenza is increasing.
a. If I wanted to control my margin of error and set it to 3% with 99% confidence, what sample size would I need to take instead of the 100?
b. Using my original sample size of 100, what would be the 99% confidence interval for the population proportion?
c. What are the null and alternative hypotheses?
d. What is the critical value at 99% confidence?
e. Calculate the test statistic (using the sample of 100).
f. Find the p-value.
g. What conclusion would be made here at the 99% confidence level?

Atechnician compares repair costs for two types of microwave ovens (type i and type ii). he believes that the repair cost for type i ovens is greater than the repair cost for type ii ovens. a sample of 6767 type i ovens has a mean repair cost of $79.79$⁢79.79. the population standard deviation for the repair of type i ovens is known to be $19.18$⁢19.18. a sample of 5555 type ii ovens has a mean repair cost of $75.24$⁢75.24. the population standard deviation for the repair of type ii ovens is known to be $21.40$⁢21.40. conduct a hypothesis test of the technician's claim at the 0.050.05 level of significance. let μ1μ1 be the true mean repair cost for type i ovens and μ2μ2 be the true mean repair cost for type ii ovens. step 2 of 4 : compute the value of the test statistic. round your answer to two decimal places.