david is a statistician. he has a sample size of 40 (which he cannot change). what element of his hypothesis…

david is a statistician. he has a sample size of 40 (which he cannot change). what element of his hypothesis test can he adjust to minimize the probability that he incorrectly rejects the null hypothesis?\no the mean of the population\no the mean of the sample\no the standard deviation of the population\no the significance level of the test

david is a statistician. he has a sample size of 40 (which he cannot change). what element of his hypothesis test can he adjust to minimize the probability that he incorrectly rejects the null hypothesis?\no the mean of the population\no the mean of the sample\no the standard deviation of the population\no the significance level of the test

Answer

Answer:

D. the significance level of the test

Explanation:

Step1: Understand Type - I error

Incorrectly rejecting the null hypothesis is a Type - I error. The probability of a Type - I error is equal to the significance level $\alpha$ of the hypothesis test.

Step2: Analyze each option

The mean of the population and the mean of the sample are parameters and statistics related to the data distribution, not directly related to controlling Type - I error. The standard deviation of the population is also a characteristic of the population and not a factor to adjust for Type - I error control. The significance level $\alpha$ is the probability of rejecting the null hypothesis when it is true. By decreasing the significance level, we can minimize the probability of incorrectly rejecting the null hypothesis.