According to the National Beer Wholesalers Association, U. S. consumers years and older consumed gallons of beer and cider per person during . A distributor in Milwaukee believes that beer and cider consumption are higher in that city. A sample of consumers years and older in Milwaukee will be taken, and the sample mean beer and cider consumption will be used to test the following null and alternative hypotheses:. H0 : µ ≤ 26.9
Ha : µ > 26.9
a. Assume the sample data led to rejection of the null hypothesis. What would be your conclusion about consumption of beer and cider in Milwaukee?b. What is the Type I error in this situation? What are the consequences of making this error?c. What is the Type II error in this situation? What are the consequences of making this error?

Step-by-step explanation:

H0 : µ ≤ 26.9

Ha : µ > 26.9

a. since the null hypothesis is rejected, we would accept the alternative hypothesis and come to the conclusion that there is enough evidence that beer and cider consumption are higher than 26.9 in the city.

b. type 1 error happens when we reject a true null hypothesis.

this error error in this question would be that our conclusion that beer and cider consumption is greater than 26.9 is not true. what is true is that it is equal to or less than 26.9.

the consequence is that is h0 is false it would be harder to reject it at a lower level of significance.

c. type ii error happens when the null hypothesis is accepted even though it is false. here, error would be that cider we accepted that cider and beer consumption is less than or equal to 26.9 when it is actually greater than 26.9

the consequence is that it would be harder to accept a true h0 at a high level of significance