chp 7 exam
The power of the decision-making process is stated by an alpha level the likelihood of rejecting a false null hypothesis the same as a null finding the likelihood of committing a Type I error
the likelihood of rejecting a fall null hypothesis
The one-sample z test is a hypothesis test used to test hypotheses concerning a single population with a known variance concerning at least one population concerning the variance in a population all of the above
concerning a single population with a known variance
Based on the effect size conventions, d = 0.60 is a small effect size medium effect size large effect size
medium effect size
A researcher obtains z = 1.45 for a one-sample z test. What is the decision for this test at a .05 level of significance? to reject the null hypothesis to retain the null hypothesis It depends on whether the test is one-tailed or two-tailed. There is not enough information to make a decision.
retain the null hypothesis
If a researcher obtains a null finding, then what is the decision? They correctly rejected the null hypothesis. They incorrectly rejected the null hypothesis. They correctly retained the null hypothesis. They failed to make a decision.
the correctly retained the null hypothesis
Increasing sample size will Increase the alpha level. Increase the likelihood of committing a Type I error. Increase the power of the decision. All of the above.
increase the power of the decision
A researcher reports that scores were higher than the mean in the population, z 1.60, p .05 (d .14). If this was a test at a .05 level of significance, then what value must be incorrectly reported? The effect size The p value The alpha level The test statistic
the p value
A researcher obtains z = 2.04 for a one-sample z test. What is the decision for this test at a .05 level of significance? to reject the null hypothesis to retain the null hypothesis It depends on whether the test is one-tailed or two-tailed. There is not enough information to make a decision.
to reject the null hypothesis
When a researcher decides to retain the null hypothesis because the rejection region was located in the wrong tail, this is called a Type I error Type II error Type III error correct decision
type III error
________ allows researchers to describe (1) how far mean scores have shifted in the population, or (2) the percentage of variance that can be explained by a given variable. significance probability power effect size
effect size
The one-sample z test is a hypothesis test used to test hypotheses concerning a single population with a known variance concerning at least one population concerning the variance in a population all of the above
all of the above
Which of the following is a scenario in which increasing sample size will increase power When the effect size is small. When the effect size is large. When the probability of a Type I error is small. All of the above.
all of the above
A researcher obtains z = -6.45. What is the decision for a one-tailed test, upper-tail critical, at a .05 level of significance? to reject the null hypothesis to retain the null hypothesis It depends on the sample size. There is not enough information to make a decision.
retain the null hypothesis
Suppose a researcher wants to make sure that the probability of committing a Type I error is less than 5%. How can the researcher control for this? Set the value for a Type II error at .05. Set the alpha level at .05. Place the rejection region in both tails. both B and C
set the alpha level at 0.5
Based on the effect size conventions, d = 0.18 is a small effect size medium effect size large effect size
small effect size
Which of the following statements regarding the null hypothesis is true? The null hypothesis always makes statements about a population parameter. A decision in hypothesis testing is made about the alternative hypothesis, not the null hypothesis. The null hypothesis is the only hypothesis stated in hypothesis testing. all of the above
the null hypothesis always makes statements about a population parameter
A researcher directly controls for the probability of a ________, but does not directly control for the probability of a ________. Type I error; alpha level Type II error; beta level Type I error; Type II error Type II error; Type I error
type I, type II
The probability of committing a Type I error is stated by ________; the probability for committing a Type II error is stated by ________. beta; alpha alpha; beta a p value; a p value the power; the power
alpha, beta
A researcher obtains z = 3.98 for a one-sample z test. If her decision is to retain the null hypothesis, then what do you know about her decision? Her decision was inconclusive. Her decision was based on a two-tailed test. Her decision resulted in a Type III error. both A and B
her decision resulted in a type III error
A method for testing a claim or hypothesis about a parameter in a population, using data measured in a sample, is called random sampling level of significance hypothesis testing guessing
hypothesis testing
A researcher reports the following result for a one-sample z test at a .05 level of significance: z 1.88, p .06 (d .25). Is this result significant? Yes, the decision is to reject the null hypothesis Yes, because the effect size is large hypothesis No, the decision is to retain the null hypothesis No, because the effect size is small hypothesis
no, the decision is to retain the null hypothesis
In hypothesis testing, a researcher can never compute a test statistic before making a decision make decisions about the null hypothesis prove that his or her hypothesis is correct know the likelihood of obtaining a sample mean if the null hypothesis were true
prove that his or her hypothesis is correct
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? The different decisions in Study 1 and Study 2 are not possible because all values were the same. The different decisions in Study 1 and Study 2 are not possible because the researcher tested the same hypothesis. The different decisions in Study 1 and Study 2 are due to an error the researcher made in the first hypothesis test. The different decisions in Study 1 and Study 2 are possible because the second test was associated with greater power to detect an effect.
the different decisions are possible because the second test was associated with a greater power to detect an effect