Which of the following is an accurate definition for the power of a statistical test?​Group of answer choices​The probability of rejecting a false null hypothesis​The probability of supporting a false null hypothesis​The probability of rejecting a true null hypothesis​The probability of supporting true null hypothesis

The power of a test is the probability of making:Group of answer choicesan incorrect decision when the null hypothesis is false.an incorrect decision when the null hypothesis is true.a correct decision when the null hypothesis is false.a correct decision when the null hypothesis is true.

What is statistical power?Review LaterThe probability of correctly rejecting the null hypothesis when the alternative hypothesis is true.The probability of committing a Type I error (false positive), which is rejecting the null hypothesis when it is true.The probability of committing a Type II error (false negative), which is failing to reject the null hypothesis when the alternative hypothesis is true.None of the above

Recall that the power of a test is the probability that we reject H_0 when H_0 is false. Which of the following are true? Select one or more answers.Group of answer choicesIf sample size increases then power increases.If H_0 is very likely to be true then the power is higher when compared to when H_0 is very likely to be false.If α increases then power increases.If the effect size increases then power increases.

Identify the three factors that determine the power of a statistical test.Select one or more:a.statistical treatmentb.null hypothesis testingc.level of statistical significanced.sample sizee.size of the treatment effectf.pobability

In hypothesis testing, if the power of a hypothesis test is 96%, which of the following statements is true about this test? a. The probability of a Type II error is 0.96. b. The probability of a Type II error is 0.04. c. The probability of a Type I error is 0.04. d. The probability of Type I error is 0.96.