Question

select true or false from each pull-down menu, depending on whether the corresponding statement is true or false. false 1. increasing the probability of a type i error also increases the probability of a type ii error false 2. if we do not reject the null hypothesis, we conclude that there is enough statistical evidence to infer that the null hypothesis is true. false 3. the probability of making a type i error and the level of significance are the same. true 4. the probability of a type i error is represented by , and is the probability of rejecting a true null hypothesis.

Answer 1

The probability of making a Type I error and the level of significance are the same. Increasing the probability of a Type I error does not necessarily increase the probability of a Type II error.

Step-by-step explanation:

A Type I error occurs when a true null hypothesis is rejected, while a Type II error occurs when a false null hypothesis is not rejected. Therefore, the statement in question is false. Increasing the probability of a Type I error does not necessarily increase the probability of a Type II error.

The statement that if we do not reject the null hypothesis, we conclude that there is enough statistical evidence to infer that the null hypothesis is true is also false. Failing to reject the null hypothesis does not necessarily imply that the null hypothesis is true.

The statement that the probability of making a Type I error and the level of significance are the same is true. The level of significance, denoted by the symbol α, represents the probability of making a Type I error.

The probability of a Type I error is represented by α, and it is the probability of rejecting a true null hypothesis. Therefore, the statement is true.