Which of the following statements about the comparison between affect size and power is correct?

Which of the following statements best represents the relationship between statistical power and effect size?

	A) Statistical power is a measure of the ability to correctly reject the null hypothesis which becomes harder to do when the effect size, or difference between groups, decreases.
	B) Statistical power is a measure of how different two groups are, and effect size measures the ability to reliably detect that difference. As power increases, effect size will also increase.
C)	Statistical power and effect size are independent and unrelated measures.
	D) Statistical power is a measure of the ability to correctly reject the null hypothesis which becomes harder to do when the effect size, or difference between groups, increases.

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1
__________ statistics are used to infer that the results from a sample are reflective of the true population scores. A) Descriptive B) Regression C) Correlated D) Inferential 2
When comparing group means, the _________ states that group means are equal. A) sampling distribution B) probability distribution C) null hypothesis D) research hypothesis 3
A sampling distribution is __________. A) based on the assumption that the null hypothesis is true B) a probability distribution C) specified by the null hypothesis D) all of these 4
Which of the following statements is FALSE? A) The analysis of variance is an extension of the t-test. B) When a study has only one independent variable with two groups, F and t2 are identical. C) The smaller the F ratio, the more likely the results are significant. D) Degrees of freedom are the number of scores free to vary once the means are known. 5
The F statistic is a ratio of two types of variance: __________ variance and error variance. A) random B) individual C) true D) systematic 6
Cohen's d expresses effect size in terms of _________ units. A) standard deviation B) range C) mean D) variance 7
A Type I error occurs when the null hypothesis is _________. A) rejected and the research hypothesis is true B) accepted, but the research hypothesis is actually true C) rejected, but the null hypothesis is actually true D) accepted, but the null hypothesis is actually false 8
Which of the following statements is TRUE? A) A very low significance level increases the chances of a Type I error. B) If the effect size is small, a Type II error is unlikely. C) When the null hypothesis is rejected, the population means are equal. D) True differences are more likely to be detected if the sample size is large. 9
If a mechanic looks at your car engine and says there is nothing wrong with it and your car breaks down when you leave the garage, what type of error did the mechanic make? A) Type I B) Type II C) Systematic error D) Matrix error 10
If the null hypothesis was rejected and there was 1 chance out of 100 that the decision was wrong, what was the alpha level in the study? A) .01 B) .10 C) .001 D) .100 11
The probability of a Type II error is related to __________. A) sample size B) significance level (alpha) C) effect size D) all of these 12
Which of the following is NOT a reason for a Type II error? A) incomprehensive instructions to participants B) a very weak manipulation of the independent variable C) using a dependent measure that is unreliable and insensitive D) large sample size 13
Dr. P is using a t-test to compare the means of two groups. There are 25 participants in each group. How many degrees of freedom are there in this test? A) 23 B) 25 C) 48 D) 50 14
How is the power of a statistical test related to the probability of a Type II error? A) Power = 1 + Type II error B) Power = Type II error x alpha level C) Power = alpha level + Type II error D) Power = 1 – Type II error 15
Which of the following is NOT a major statistical software program? A) XSPS B) SPSS C) SAS D) Minitab 16
A researcher believes that students who stay up all night cramming the night before an exam will not do as well as those who get a full 7 hours of sleep the night before the test. What is the null hypothesis in this example? A) Hours of sleep the night before a test impacts exam performance B) Students who sleep for 7 hours the night before a test will do better than those who stay up all night cramming. C) Hours of sleep the night before an exam will not impact exam performance. D) Cramming is not a good study method. 17
The most common alpha level probability used is A) .50 B) .25 C) .10 D) .05 18
Dr. Data randomly assigned 10 participants to drink a caffeinated beverage and another 10 people to drink uncaffeinated beverage. He then recorded their average driving speed over a 10 minute period. Caffeinated drivers averaged 50 mph with a variance of 20 and uncaffeinated drivers averaged 30 mph with a variance of 20. What is t? A) 20 B) 10 C) 5 D) 2 19
A researcher is interested in the effects of distraction on driving. He randomly assigns 30 participants to either drive while texting, while listening to the radio, or by talking on the phone. The number of mistakes each participant makes is recorded. What type of analysis should be done on the collected data? A) t-test B) F-test C) chi square D) power test 20
A researcher calculated a t value of 10 with 20 degrees of freedom. What is the effect size in this study? A) .91 B) .58 C) .71 D) 1.10 21
Which of the following is false? A) The alpha level you choose indicates how confident you wish to be when making decisions about significance. B) Significant results are more likely if the effect size is large. C) Significant results are more likely when sample sizes are large. D) Confidence intervals are influenced by the size of the sample variances.

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