Aspirin A bottle contains a label stating that it contains Spring Valley pills with 500 mg of vitamin C, and another bottle contains a label stating that it contains Bayer 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 Spring Valley vitamin C claim or rejection of the Bayer aspirin claim? 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 aboutis more serious because the wrongV dosage could cause more serious adverse reactions than a wrongdosage. It would be wise to use asignificance level for testing the claim about the aspirin.

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 greater significance level for testing the claim about the aspirin.

Step-by-step explanation:

The wrong dosage of aspirin will cause more damage than a wrong dosage of vitamin C. Then, if we perform an hypothesis test for each mean, the rejection of the claim about the aspirin content is more serious than the vitamin C content.

In the case of the aspirin, we want to minimize the Type II error (accepting a false null hypothesis). This can be achieved increasing the sample size or/and increasing the significance level. Then, a significative difference between the claimed content and the sample content will be easily detected.

the smallest possible measurement of the width is 14 feet

step-by-step explanation:

let's assume length of parallelogram is 'l'

width of parallelogram is 'w'

the perimeter of a parallelogram must be no less than 40 feet

so, we get

we are given

length of parallelogram is 6 feet

so,

l=6

we can plug it

now, we can solve for w

subtract both sides by 12

divide both sides by 2

and we get

so,

the smallest possible measurement of the width is 14 feet