Question 1

When a false null hypothesis is rejected,the researcher has made a Type II error.

Accepted Answer

When a false null hypothesis is rejected, it means that the researcher has correctly identified a significant effect or difference. A Type II error occurs when a true null hypothesis is not rejected, which means there is a failure to identify a significant effect or difference that actually exists.

Question 2

Generally speaking,the hypotheses that business researchers want to prove are stated in the alternative hypothesis.

Accepted Answer

The alternative hypothesis is the statement that the researcher wants to prove or support. It is the opposite of the null hypothesis, which is the default assumption that there is no significant relationship between variables.

Question 3

Reach a statistical conclusion in hypothesis testing problems about a population proportion using the z statistic.

Accepted Answer

Included in this chapter were hypothesis tests for a single mean when σ is known and when σ is unknown,a test of a single population proportion,and a test for a population variance.Three different analytic approaches were presented: (1)the standard method, (2)the p value method,and (3)the critical value method.

Question 4

Hypotheses are tentative explanations of a principle operating in nature.

Accepted Answer

Hypotheses are tentative explanations that are subject to testing and verification, and they are used to explain principles operating in nature.

Question 5

Reach a statistical conclusion in hypothesis testing problems about a population mean with a known population standard deviation using the z statistic.

Accepted Answer

The answer of Reach a statistical conclusion in hypothesis testing...

Question 6

Reach a statistical conclusion in hypothesis testing problems about a population variance using the chi-square statistic.

Accepted Answer

The answer of Reach a statistical conclusion in hypothesis testing...

Question 7

When a true null hypothesis is rejected,the researcher has made a Type I error.

Accepted Answer

This statement is true. A Type I error occurs when the null hypothesis is actually true, but the researcher erroneously rejects it based on their sample data. This means that they have mistakenly concluded that there is a significant effect or relationship when there really isn't one.

Question 8

Whenever hypotheses are established such that the alternative hypothesis is "not equal to",the hypothesis test would be a two-tailed test.

Accepted Answer

This is true because a hypothesis that is "not equal to" means that the researcher is testing for differences in both directions, so the test would need to examine both tails of the distribution.

Question 9

Power is equal to (1 -$\beta$),the probability of a test rejecting the null hypothesis that is indeed false.

Accepted Answer

The statement is true. Power of a test is the probability of rejecting the null hypothesis when it is indeed false. It is calculated as 1 minus the probability of type II error, which is represented as (1 -F1F1F1S1F1F1F10).

Question 10

The rejection region for a hypothesis test becomes smaller if the level of significance is changed from 0.01 to 0.05.

Accepted Answer

The rejection region actually becomes larger as the level of significance increases from 0.01 to 0.05.

Question 11

Whenever hypotheses are established such that the alternative hypothesis is ">",then this would be a two-tailed test.

Accepted Answer

If the alternative hypothesis is ">", then it is a one-tailed test in the direction of the inequality. A two-tailed test would have an alternative hypothesis that is "not equal to".

Question 12

Reach a statistical conclusion in hypothesis testing problems about a population mean with an unknown population standard deviation using the t statistic.

Accepted Answer

The answer of Reach a statistical conclusion in hypothesis testing...

Question 13

The first step in testing a hypothesis is to establish a true null hypothesis and a false alternative hypothesis.

Accepted Answer

The first step is to establish a null hypothesis (H0) that assumes no effect or no difference, and an alternative hypothesis (H1) that proposes an effect, difference, or relationship. The null is not assumed to be true or false initially; it's a starting point for testing.

Question 14

Develop both one- and two-tailed null and alternative hypotheses that can be tested in a business setting by examining the rejection and nonrejection regions in light of Type I and Type II errors.

Accepted Answer

The answer of Develop both one- and two-tailed null and...

Question 15

The probability of committing a Type I error is called the power of the test.

Accepted Answer

The probability of committing a Type I error is called the level of significance. The power of a test is the probability of correctly rejecting the null hypothesis when it is false, in other words, the ability of the test to detect a true effect.

Question 16

In testing hypotheses,the researcher initially assumes that the alternative hypothesis is true and uses the sample data to reject it.

Accepted Answer

In hypothesis testing, the researcher initially assumes that the null hypothesis is true (not the alternative hypothesis). The sample data is then used to either reject or fail to reject the null hypothesis.

Question 17

The null and the alternative hypotheses must be mutually exclusive and collectively exhaustive.

Accepted Answer

The null and alternative hypotheses must be mutually exclusive, meaning that they cannot both be true at the same time. Additionally, they must be collectively exhaustive, meaning that one of the two hypotheses must be true. This ensures that the hypothesis test is complete and does not leave any other possibilities unaccounted for.

Question 18

When a researcher fails to reject a false null hypothesis,a Type II error has been committed.

Accepted Answer

A Type II error occurs when the null hypothesis is false, but the researcher fails to reject it, mistakenly concluding there is not enough evidence to support the alternative hypothesis.

Question 19

The rejection and nonrejection regions are divided by a point called the critical value.

Accepted Answer

This is true. The critical value separates the values of a test statistic that lead to rejection of the null hypothesis from those that do not.

Question 20

Solve for possible Type II errors when failing to reject the null hypothesis.

Accepted Answer

The answer of Solve for possible Type II errors when...

Quiz 9: Statistical Inference: Hypothesis Testing for Single Populations

When a false null hypothesis is rejected,the researcher has made a Type II error.

Generally speaking,the hypotheses that business researchers want to prove are stated in the alternative hypothesis.

Reach a statistical conclusion in hypothesis testing problems about a population proportion using the z statistic.

Hypotheses are tentative explanations of a principle operating in nature.

Reach a statistical conclusion in hypothesis testing problems about a population mean with a known population standard deviation using the z statistic.

Reach a statistical conclusion in hypothesis testing problems about a population variance using the chi-square statistic.

When a true null hypothesis is rejected,the researcher has made a Type I error.

Whenever hypotheses are established such that the alternative hypothesis is "not equal to",the hypothesis test would be a two-tailed test.

Power is equal to (1 - $\beta$ ),the probability of a test rejecting the null hypothesis that is indeed false.

The rejection region for a hypothesis test becomes smaller if the level of significance is changed from 0.01 to 0.05.

Whenever hypotheses are established such that the alternative hypothesis is ">",then this would be a two-tailed test.

Reach a statistical conclusion in hypothesis testing problems about a population mean with an unknown population standard deviation using the t statistic.

The first step in testing a hypothesis is to establish a true null hypothesis and a false alternative hypothesis.

Develop both one- and two-tailed null and alternative hypotheses that can be tested in a business setting by examining the rejection and nonrejection regions in light of Type I and Type II errors.

The probability of committing a Type I error is called the power of the test.

In testing hypotheses,the researcher initially assumes that the alternative hypothesis is true and uses the sample data to reject it.

The null and the alternative hypotheses must be mutually exclusive and collectively exhaustive.

When a researcher fails to reject a false null hypothesis,a Type II error has been committed.

The rejection and nonrejection regions are divided by a point called the critical value.

Solve for possible Type II errors when failing to reject the null hypothesis.

Quiz 9: Statistical Inference: Hypothesis Testing for Single Populations

When a false null hypothesis is rejected,the researcher has made a Type II error.

Generally speaking,the hypotheses that business researchers want to prove are stated in the alternative hypothesis.

Reach a statistical conclusion in hypothesis testing problems about a population proportion using the z statistic.

Hypotheses are tentative explanations of a principle operating in nature.

Reach a statistical conclusion in hypothesis testing problems about a population mean with a known population standard deviation using the z statistic.

Reach a statistical conclusion in hypothesis testing problems about a population variance using the chi-square statistic.

When a true null hypothesis is rejected,the researcher has made a Type I error.

Whenever hypotheses are established such that the alternative hypothesis is "not equal to",the hypothesis test would be a two-tailed test.

Power is equal to (1 - β\betaβ ),the probability of a test rejecting the null hypothesis that is indeed false.

The rejection region for a hypothesis test becomes smaller if the level of significance is changed from 0.01 to 0.05.

Whenever hypotheses are established such that the alternative hypothesis is ">",then this would be a two-tailed test.

Reach a statistical conclusion in hypothesis testing problems about a population mean with an unknown population standard deviation using the t statistic.

The first step in testing a hypothesis is to establish a true null hypothesis and a false alternative hypothesis.

Develop both one- and two-tailed null and alternative hypotheses that can be tested in a business setting by examining the rejection and nonrejection regions in light of Type I and Type II errors.

The probability of committing a Type I error is called the power of the test.

In testing hypotheses,the researcher initially assumes that the alternative hypothesis is true and uses the sample data to reject it.

The null and the alternative hypotheses must be mutually exclusive and collectively exhaustive.

When a researcher fails to reject a false null hypothesis,a Type II error has been committed.

The rejection and nonrejection regions are divided by a point called the critical value.

Solve for possible Type II errors when failing to reject the null hypothesis.

Power is equal to (1 - $\beta$ ),the probability of a test rejecting the null hypothesis that is indeed false.