A consumer analyst asks participants to rate the health benefits of two health drinks-EnerG and Supreme. EnerG is rated more nutritive with a mean of 5.5 than Supreme, which is found to have a mean of 4.3. The Type II error would be to conclude that EnerG is:

a. more nutritious than Supreme when a true difference in health benefits exists.

b. no more nutritious than Supreme when EnerG actually provides more health benefits.

c. no more nutritious than Supreme when no difference in health benefits exists.

d. more nutritious than Supreme when the two brands provide similar health benefits.

The Type II error would be to conclude that EnerG is no more nutritious than Supreme when Energy actually provides more health benefits.

Option b

Explanation:

Type II error sometimes referred to as beta error is a term in statistics that doesn't reject the false-null hypothesis. It occurs when one refuses to reject the false null hypothesis. In this type of error, the false findings are accepted as true.

It also confirms two different scenarios as similar even though they are different. It can be reduced by adjusting the criteria of the null hypothesis by increasing tolerance with caution to ensure that the error type doesn't end up being Type I error.