Answer:
The answer is option A) To reduce her risk of making a Type II error, she should Increase the number of local consumers she will sample
Step-by-step explanation:
A type II error is sometimes called a beta error because it confirms an idea that should have been rejected, claiming the two observances are the same, even though they are different. A type II error is essentially a false positive.
A type II error can be reduced by making more stringent criteria for rejecting a null hypothesis such as:
- Increasing the the sample size used in the Test: this is a strategy used to increase the power of the test and reduce the error to a considerable amount.
- Increasing the significance level: choosing a higher level of significance is important for double checking and which increases accuracy.