Statistics Chapter 9 MC Questions

The level of significance a. can be any positive value b. can be any value c. is (1 - confidence level) d. can be any value between -1.96 to 1.96

c. is (1 - confidence level)

The level of significance in hypothesis testing is the probability of a. accepting a true null hypothesis b. accepting a false null hypothesis c. rejecting a true null hypothesis d. None of these alternatives is correct.

c. rejecting a true null hypothesis

Which of the following does not need to be known in order to compute the p-value? a. knowledge of whether the test is one-tailed or two-tailed b. the value of the test statistic c. the level of significance d. None of these alternatives is correct.

c. the level of significance

The probability of making a Type I error is denoted by a. α b. β c. 1 - α d. 1 - β

a. α

21.When the following hypotheses are being tested at a level of significance of α H0: μ >= 500 Ha: μ < 500 the null hypothesis will be rejected if the p-value is a. <= α b. > α c. > α/2 d. <= 1-α/2

a. <= α

In order to test the following hypotheses at an α level of significance H0: μ <= 800 Ha: μ > 800 the null hypothesis will be rejected if the test statistic Z is a. >= Zα b. < Zα c. < -Zα d. = α

a. >= Zα

An assumption made about the value of a population parameter is called a a. Hypothesis b. Conclusion c. Confidence d. Significance

a. Hypothesis

What type of error occurs if you fail to reject H0 when, in fact, it is not true? a. Type II b. Type I c. either Type I or Type II, depending on the level of significance d. either Type I or Type II, depending on whether the test is one tail or two tail

a. Type II

The error of rejecting a true null hypothesis is a. a Type I error b. a Type II error c. is the same as β d. committed when not enough information is available

a. a Type I error

A Type II error is committed when a. a true alternative hypothesis is mistakenly rejected b. a true null hypothesis is mistakenly rejected c. the sample size has been too small d. not enough information has been available

a. a true alternative hypothesis is mistakenly rejected

For a lower tail test, the p-value is the probability of obtaining a value for the test statistic a. at least as small as that provided by the sample b. at least as large as that provided by the sample c. at least as small as that provided by the population d. at least as large as that provided by the population.

a. at least as small as that provided by the sample

The p-value is a probability that measures the support (or lack of support) for the a. null hypothesis b. alternative hypothesis c. either the null or the alternative hypothesis d. sample statistic

a. null hypothesis

When the p-value is used for hypothesis testing, the null hypothesis is rejected if a. p-value <= α b. α < p-value c. p-value >= α d. p-value = 1 - α

a. p-value <= α

In the hypothesis testing procedure, α is a. the level of significance b. the critical value c. the confidence level d. 1 - level of significance

a. the level of significance

The level of significance is the a. maximum allowable probability of Type II error b. maximum allowable probability of Type I error c. same as the confidence coefficient d. same as the p-value

b. maximum allowable probability of Type I error

In hypothesis testing if the null hypothesis is rejected, a. no conclusions can be drawn from the test b. the alternative hypothesis is true c. the data must have been accumulated incorrectly d. the sample size has been too small

b. the alternative hypothesis is true

In hypothesis testing, the tentative assumption about the population parameter is a. the alternative hypothesis b. the null hypothesis c. either the null or the alternative d. None of these alternatives is correct.

b. the null hypothesis

In hypothesis testing, a. the smaller the Type I error, the smaller the Type II error will be b. the smaller the Type I error, the larger the Type II error will be c. Type II error will not be effected by Type I error d. the sum of Type I and Type II errors must equal to 1

b. the smaller the Type I error, the larger the Type II error will be

For a two-tail test, the p-value is the probability of obtaining a value for the test statistic as a. likely as that provided by the sample b. unlikely as that provided by the sample c. likely as that provided by the population d. unlikely as that provided by the population

b. unlikely as that provided by the sample

The probability of making a Type II error is denoted by a. α b. β c. 1 - α d. 1 - β

b. β

The sum of the values of α and β a. always add up to 1.0 b. always add up to 0.5 c. is the probability of Type II error d. None of these alternatives is correct.

d. None of these alternatives is correct.

The power curve provides the probability of a. correctly accepting the null hypothesis b. incorrectly accepting the null hypothesis c. correctly rejecting the alternative hypothesis d. correctly rejecting the null hypothesis

d. correctly rejecting the null hypothesis

The p-value a. is the same as the Z statistic b. measures the number of standard deviations from the mean c. is a distance d. is a probability

d. is a probability

The probability of committing a Type I error when the null hypothesis is true is a. the confidence level b. β c. greater than 1 d. the Level of Significance

d. the Level of Significance

In hypothesis testing if the null hypothesis has been rejected when the alternative hypothesis has been true, a. a Type I error has been committed b. a Type II error has been committed c. either a Type I or Type II error has been committed d. the correct decision has been made

d. the correct decision has been made