Question 1

A null finding is a decision to retain a null hypothesis that is correct.

Accepted Answer

A null finding occurs when a study fails to reject a null hypothesis, indicating that there is no significant difference between groups or no significant relationship between variables. This decision to retain the null hypothesis would be correct if there truly is no effect or relationship in the population being studied.

Question 2

A researcher tests a hypothesis to prove whether or not his or her hypothesis is correct.

Accepted Answer

A researcher tests a hypothesis to determine if there is enough evidence to support or reject it, not to prove it correct or incorrect.

Question 3

Researchers directly control for the probability of committing a Type II error.

Accepted Answer

Researchers control for the probability of committing a Type II error indirectly by choosing the sample size and the power of the test, not directly.

Question 4

Rejecting a true null hypothesis is a Type I error.

Accepted Answer

Rejecting a true null hypothesis means that the result is significant when it should not be, which is known as a Type I error.

Question 5

The null hypothesis and alternative hypotheses are statements about parameters in the population.

Accepted Answer

The null hypothesis and alternative hypotheses are statements about population parameters, such as population means or proportions.

Question 6

A researcher computes a one-sample z test in two studies.Both studies used the same alpha level,placed the rejection region in both tails,and measured the same sample mean.The researcher selects a sample of 30 participants in Study 1 and decides to retain the null hypothesis.She selects a sample of 60 participants in Study 2 and decides to reject the null hypothesis.Which of the following is the best explanation for why the decision was different in Study 1 and Study 2?

Accepted Answer

The different decisions in Study 1 and Study 2 are due to the fact that Study 2 had a larger sample size, which increased the power of the test to detect an effect. This resulted in the rejection of the null hypothesis in Study 2, whereas the null hypothesis was retained in Study 1.

Question 7

A researcher reports that the standard deviation in Population A is $\sigma$ = 2.3 and the standard deviation in Population B is $\sigma$ = 4.3.Which population is associated with the highest power to detect an effect?

Accepted Answer

A smaller standard deviation indicates less variability in the data, which leads to a greater power to detect an effect. Therefore, Population A, with a smaller standard deviation, is associated with a higher power to detect an effect.

Question 8

Increasing sample size will

Accepted Answer

Increasing the sample size increases the power of the decision by reducing sampling error and increasing the precision of the estimate, without affecting the alpha level or the likelihood of committing a Type I error. Therefore, option C is the correct choice.

Question 9

Is a one-sample z test reported differently for one-tailed and two-tailed tests?

Accepted Answer

The same values are reported for one-tailed and two-tailed tests in a one-sample z test. The values include the test statistic, degrees of freedom, p-value or critical value, and sample mean and standard deviation. The reporting of significant results does not affect the reporting of these values, and neither does the effect size.

Question 10

A researcher conducts two studies.Each study was a one-sample z test.Both studies placed the rejection region in both tails and measured the same sample mean.The beta level in Study 1 was larger than the beta level used in Study 2.Which study is associated with greater power to detect an effect?

Accepted Answer

The larger beta level in Study 1 indicates a higher probability of a Type II error, which means that there is a lower probability of correctly detecting an effect. Therefore, Study 2 with the smaller beta level is associated with greater power to detect an effect.

Question 11

The probability of correctly rejecting a false null hypothesis is called the power of the decision-making process.

Accepted Answer

This statement is true. The power of a test is the probability of correctly rejecting a false null hypothesis, which means it measures the ability of the decision-making process to detect a true difference or effect when it exists. A higher power indicates a better test, as it reduces the risk of making a type II error, which is failing to reject a false null hypothesis.

Question 12

The alpha level is the likelihood of committing a Type I error.

Accepted Answer

The alpha level is the threshold for rejecting the null hypothesis, and the probability of committing a Type I error is equal to the alpha level. Therefore, the statement is true.

Question 13

A researcher reports that scores were higher than the mean in the population,z = 1.60,p = .05 (d = 0.14).If this was a test at a .05 level of significance,then what value must be incorrectly reported?

Accepted Answer

If the researcher is reporting that scores are higher than the mean in the population with a p-value of .05, this means that they are reporting the results of a hypothesis test. The incorrectly reported value must be either the p-value or the test statistic, as these are the two values that are directly calculated from the sample data and used to make a decision about the null hypothesis. The effect size (d = 0.14) and the alpha level (.05) are not directly calculated from the sample data, so these values are less likely to be incorrect.

Question 14

One step to hypothesis testing is to set the criteria for a decision.

Accepted Answer

Setting the criteria for a decision is an important step in hypothesis testing. It involves determining a significance level (alpha) and using it to determine whether the test statistic falls within the rejection region or the non-rejection region. Based on this determination, a decision can be made to either reject or fail to reject the null hypothesis.

Question 15

Which of the following is a scenario in which increasing sample size will increase power?

Accepted Answer

Increasing the sample size increases the power of a statistical test in all these scenarios: when the effect size is small (making it easier to detect the effect), when the effect size is large (further improving the likelihood of detecting the effect), and when the probability of a Type I error (alpha) is small (since increasing sample size helps in achieving significance despite a lower alpha).

Question 16

When reporting the results of a one-sample z test using APA format,the ______ does not need to be reported.

Accepted Answer

The critical values are not required to be reported in the APA format for reporting the results of a one-sample z test. The test statistic, p-value, and effect size are important results that should be included in the report.

Question 17

The level of significance in hypothesis testing in the behavioral sciences is typically set at .05.

Accepted Answer

A level of significance of .05 is commonly used in hypothesis testing in the behavioral sciences. This means that there is a 5% chance of obtaining a result as extreme or more extreme than the one observed, assuming the null hypothesis is true. This is known as the alpha level or the probability of a Type I error.

Question 18

Following the steps to hypothesis testing allows researchers to make decisions about parameters in a sample using statistics measured in a population.

Accepted Answer

Hypothesis testing involves making decisions about population parameters based on statistics measured in a sample, not the other way around.

Question 19

A researcher reports the following result for a one-sample z test at a .05 level of significance: z = 1.88,p = .06 (d = 0.25).Is this result significant?

Accepted Answer

The p-value is greater than the level of significance of .05, therefore we fail to reject the null hypothesis. Additionally, the effect size (d = 0.25) is considered small, which does not provide much evidence for a significant difference.

Question 20

A researcher conducts a study,but has low power to detect an effect.Which of the following is one way in which the research can increase power?

Accepted Answer

Increasing the sample size will increase the power of the study by reducing the variability of the data and making it easier to detect a significant effect. Making the alpha level smaller may decrease the chance of a Type I error, but it does not increase the power of the study. Studying a population with a larger standard deviation may actually decrease the power of the study because it increases the variability of the data. Conducting the study again with the same sample size is not likely to increase power unless there were some modifications made to the study design or analysis.

Quiz 8: Hypothesis Testing: Significance,effect Size,and Power

A null finding is a decision to retain a null hypothesis that is correct.

A researcher tests a hypothesis to prove whether or not his or her hypothesis is correct.

Researchers directly control for the probability of committing a Type II error.

Rejecting a true null hypothesis is a Type I error.

The null hypothesis and alternative hypotheses are statements about parameters in the population.

A researcher reports that the standard deviation in Population A is $\sigma$ = 2.3 and the standard deviation in Population B is $\sigma$ = 4.3.Which population is associated with the highest power to detect an effect?

Increasing sample size will

Is a one-sample z test reported differently for one-tailed and two-tailed tests?

A researcher conducts two studies.Each study was a one-sample z test.Both studies placed the rejection region in both tails and measured the same sample mean.The beta level in Study 1 was larger than the beta level used in Study 2.Which study is associated with greater power to detect an effect?

The probability of correctly rejecting a false null hypothesis is called the power of the decision-making process.

The alpha level is the likelihood of committing a Type I error.

A researcher reports that scores were higher than the mean in the population,z = 1.60,p = .05 (d = 0.14) .If this was a test at a .05 level of significance,then what value must be incorrectly reported?

One step to hypothesis testing is to set the criteria for a decision.

Which of the following is a scenario in which increasing sample size will increase power?

When reporting the results of a one-sample z test using APA format,the ______ does not need to be reported.

The level of significance in hypothesis testing in the behavioral sciences is typically set at .05.

Following the steps to hypothesis testing allows researchers to make decisions about parameters in a sample using statistics measured in a population.

A researcher reports the following result for a one-sample z test at a .05 level of significance: z = 1.88,p = .06 (d = 0.25) .Is this result significant?

A researcher conducts a study,but has low power to detect an effect.Which of the following is one way in which the research can increase power?

Quiz 8: Hypothesis Testing: Significance,effect Size,and Power

A null finding is a decision to retain a null hypothesis that is correct.

A researcher tests a hypothesis to prove whether or not his or her hypothesis is correct.

Researchers directly control for the probability of committing a Type II error.

Rejecting a true null hypothesis is a Type I error.

The null hypothesis and alternative hypotheses are statements about parameters in the population.

A researcher reports that the standard deviation in Population A is σ\sigmaσ = 2.3 and the standard deviation in Population B is σ\sigmaσ = 4.3.Which population is associated with the highest power to detect an effect?

Increasing sample size will

Is a one-sample z test reported differently for one-tailed and two-tailed tests?

A researcher conducts two studies.Each study was a one-sample z test.Both studies placed the rejection region in both tails and measured the same sample mean.The beta level in Study 1 was larger than the beta level used in Study 2.Which study is associated with greater power to detect an effect?

The probability of correctly rejecting a false null hypothesis is called the power of the decision-making process.

The alpha level is the likelihood of committing a Type I error.

A researcher reports that scores were higher than the mean in the population,z = 1.60,p = .05 (d = 0.14) .If this was a test at a .05 level of significance,then what value must be incorrectly reported?

One step to hypothesis testing is to set the criteria for a decision.

Which of the following is a scenario in which increasing sample size will increase power?

When reporting the results of a one-sample z test using APA format,the ______ does not need to be reported.

The level of significance in hypothesis testing in the behavioral sciences is typically set at .05.

Following the steps to hypothesis testing allows researchers to make decisions about parameters in a sample using statistics measured in a population.

A researcher reports the following result for a one-sample z test at a .05 level of significance: z = 1.88,p = .06 (d = 0.25) .Is this result significant?

A researcher conducts a study,but has low power to detect an effect.Which of the following is one way in which the research can increase power?

A researcher reports that the standard deviation in Population A is $\sigma$ = 2.3 and the standard deviation in Population B is $\sigma$ = 4.3.Which population is associated with the highest power to detect an effect?