Question

2)

A bottle contains a label stating that it contains pills with 500 mg of vitamin C, and another bottle contains a label stating that it contains pills with 325 mg of aspirin. When testing claims about the mean contents of the pills, which would have more serious implications: rejection of the vitamin C claim or rejection of the aspirin claim? Considering only a type I error and using the same sample size, is it wise to use the same significance level for hypothesis tests about the mean amount of vitamin C and the mean amount of aspirin? Rejection of the claim about is more serious because the wrong dosage could cause more serious adverse reactions than a wrong dosage. It would be wise to use a significance level for testing the claim about the aspirin.
(aspirin) (vitamin c) (Aspirin) (Larger)   

(vitamin C) (aspirin)   (vitamin C) (smaller)

3)

a. This is a (two tailed) (right tailed) (left tailed) test.

Answer 1

2)

Rejection of the claim about aspirin is more serious because the wrong aspirin dosage could cause more serious adverse reactions than a wrong vitamin C dosage. It would be wise to use a different significance level for testing the claim about the aspirin.

3)

Alpha = 0.05

Null and Alternate Hypothesis

H₀: p = 0.157

H_a: p <> 0.157

a)

This is a two-tailed test.

b)

Test Statistic

z = 1.78

P(z>|1.78|) =2*P(z<-1.78) = 2* 0.0375 = 0.075

Result

Since the p-value is greater than 0.05, we fail to reject the null hypothesis.

c)

Option A: Fail to Reject H0. There is not sufficient evidence to support the claim that p <> 0.157