Question 1 of 25
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1.0 Points |
Effect size is a measure of:
A.the difference between individual members of a sample |
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B.the extent to which two populations overlap |
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C.the extent to which two populations do not overlap |
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D.the statistical significance of a research study |
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Question 2 of 25
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1.0 Points |
Which of the following is NOT a correct statement about effect size of a study finding:
A.It provides much information about statistical significance. |
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B.It is a standardized measure of lack of overlap between populations. |
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C.It increases with greater differences between means. |
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D.It can be converted to a standardized effect size. |
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Question 3 of 25
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1.0 Points |
According to Cohen’s conventions, for research that compares means, a large effect size in which only about 53% of the populations of individuals overlap would be:
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Question 4 of 25
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1.0 Points |
Some IQ tests have a standard deviation of 16 points. If an experimental procedure produced an increase of 3.2 IQ points, the effect size would represent a __________ effect size.
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Question 5 of 25
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1.0 Points |
A standard verbal memory test is known to have a standard deviation of 10 points. If an experimental procedure produced an increase of 8 points, the effect size would represent a __________ effect size.
A.small |
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B.medium |
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C.large |
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D.unable to determine without additional information |
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Question 6 of 25
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1.0 Points |
In what way is effect size most comparable to a Z score?
A.It can range from 1 to +1 |
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B.It provides a direct indication of statistical significance |
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C.It provides a standard for comparison for results across studies, even studies using different measures |
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D.All of the above |
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Question 7 of 25
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1.0 Points |
Cohen has proposed some effect-size conventions based on the effects observed in psychology research in general because:
A.researchers frequently need to decide whether the effect size that they have found allows them to reject the null hypothesis |
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B.it is usually difficult to know how big an effect to expect from a given experiment |
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C.Cohen originally developed the relevant scales |
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D.they are more accurate than figuring a minimum meaningful difference |
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Question 8 of 25
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1.0 Points |
The effect size conventions proposed by Cohen are useful to researchers for:
A.predicting the value of the measured variable to use for the experimental condition |
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B.evaluating research results to determine if they are statistically significant |
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C.predicting the effect of a study on various populations |
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D.determining the power of a planned study |
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Question 9 of 25
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1.0 Points |
A statistical method for combining effect sizes from different studies is known as:
A.combination analysis |
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B.comparison analysis |
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C.multivariate analysis |
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D.meta-analysis |
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Question 10 of 25
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1.0 Points |
Reviews of a collection of studies on a particular topic that use meta-analyses represent an alternative to traditional __________ articles. These traditional articles describe and evaluate each study and then attempt to draw some overall conclusion.
A.general educational method |
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B.computer-assisted research |
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C.engagement goal setting |
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D.narrative literature review |
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Question 11 of 25
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1.0 Points |
It is useful to understand statistical power for which of the following reasons?
A.Determining the number of participants to use in an experiment |
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B.Making sense of findings in research articles |
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C.Understanding the implications of a study that is not statistically significant |
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D.All of the above |
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Question 12 of 25
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1.0 Points |
If statistical power for a given research study is .40, one can say that: “Assuming the researcher’s prediction is correct, the researcher has a __________ chance of attaining statistically significant results.”
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Question 13 of 25
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1.0 Points |
When a study has only a small chance of being significant even if the research hypothesis is true, the study is said to have:
A.low power |
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B.low probability |
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C.low market value |
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D.low sample size |
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Question 14 of 25
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1.0 Points |
Standard power tables are useful for:
A.directly determining the power of an experiment |
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B.determining the predicted score (but not the variance) for the group exposed to the experimental manipulation |
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C.determining the predicted effect size of a proposed experiment |
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D.determining the probability of falsely accepting the research hypothesis |
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Question 15 of 25
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1.0 Points |
Effect size is one of the two major factors that contribute to power. Another factor is:
A.the sample’s standard deviation |
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B.the minimum meaningful difference |
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C.the sample size |
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D.the mean of the known population |
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Question 16 of 25
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1.0 Points |
A researcher may not be able to change the effect size of a planned study to increase power. Another aspect of a planned study that the researcher can usually change to increase power is:
A.the sample size |
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B.the beta level |
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C.the population parameters |
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D.the sample mean |
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Question 17 of 25
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1.0 Points |
In actual practice, the usual reason for determining power before conducting a study is to:
A.eliminate the possibility that a mistake may occur |
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B.ensure that regardless of whether the research hypothesis is true, the experiment will yield a significant result |
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C.determine the number of participants needed to have a reasonable chance of getting a significant result if the research hypothesis is true |
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D.recognize the likelihood that the experiment will need to be repeated |
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Question 18 of 25
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1.0 Points |
What effect will using a one-tailed test over a two-tailed test have on power (presuming the true population difference is in the expected direction)?
A.it will increase power |
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B.it will have no effect on power |
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C.it will decrease power |
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D.power cannot be calculated if a one-tailed test is used |
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Question 19 of 25
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1.0 Points |
Using a two-tailed test makes it __________ to get significance on any one tail. Thus, keeping everything else the same, power __________ with a two-tailed test than with a one-tailed test.
A.easier; more |
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B.harder; less |
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C.easier; less |
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D.harder; more |
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Question 20 of 25
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1.0 Points |
If the research hypothesis is true, but the study has a low level of power:
A.there is a high probability that the study will have a significant result |
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B.the probability of getting a significant result is low |
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C.the null hypothesis will almost certainly be rejected |
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D.the significance level selected is probably too lenient (for example, .10 instead of .05) |
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Question 21 of 25
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1.0 Points |
Practical significance is a combination of statistical significance and:
A.effect size |
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B.the level of measurement (whether it is equal interval or ordinal) |
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C.the population parameters |
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D.the amount over or under that level that the sample scored |
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Question 22 of 25
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1.0 Points |
In statistics, we cannot state that the research hypothesis is ever definitely false. However, if one fails to reject the null hypothesis in a study with a high level of power, this allows us to:
A.suspect that the research hypothesis may still be true |
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B.conclude that the research hypothesis is most likely false |
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C.make no statements about the research hypothesis |
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D.reject the notion that the effect size has anything to do with statistical significance |
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Question 23 of 25
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1.0 Points |
What is the most likely explanation for why a study with a very small effect size came out significant?
A.the study had a large sample size |
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B.the study had a large population standard deviation |
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C.the researcher used an insensitive hypothesis-testing procedure |
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D.the researcher used a two-tailed test |
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Question 24 of 25
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1.0 Points |
When judging a study’s results, there are two important questions. They are:
A.How large is the power and how competent are the researchers? |
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B.How stringent is the significance level and how small is the effect size? |
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C.Is the result statistically significant and is the effect size large enough for the results to be meaningful? |
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D.Is the study replicable and can we draw conclusions despite not having attained statistical significance? |
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Question 25 of 25
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1.0 Points |
If the results of a study are not statistically significant and the sample size is large, then:
A.the result is very important |
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B.the result proves the null hypothesis |
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C.the research hypothesis is probably false |
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D.the result proves the research hypothesis |
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