Deck 15: Power
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Deck 15: Power
1
All other things being equal, one study will have more power than another study if
A) it has more subjects.
B) it controls error variance better.
C) it compares groups that are more extreme.
D) all of the above
A) it has more subjects.
B) it controls error variance better.
C) it compares groups that are more extreme.
D) all of the above
all of the above
2
The effect size can best be thought of as
A) the size of the largest mean.
B) the size of the difference between means in standard deviation units.
C) a mixture of the size of the difference and the sample size.
D) the largest difference we would hope to find.
A) the size of the largest mean.
B) the size of the difference between means in standard deviation units.
C) a mixture of the size of the difference and the sample size.
D) the largest difference we would hope to find.
the size of the difference between means in standard deviation units.
3
When we are worrying about power we are most concerned with
A) a Type I error.
B) a Type II error.
C) the right answer to the wrong question.
D) none of the above
A) a Type I error.
B) a Type II error.
C) the right answer to the wrong question.
D) none of the above
a Type II error.
4
In general, power increases as
A) the difference between the means decreases.
B) the sample size increases.
C) the variance increases.
D) None of the above is correct.
A) the difference between the means decreases.
B) the sample size increases.
C) the variance increases.
D) None of the above is correct.
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5
Sometimes different experimenters find different results because of
A) chance.
B) small sample sizes.
C) "the cruel hand of fate."
D) all of the above
A) chance.
B) small sample sizes.
C) "the cruel hand of fate."
D) all of the above
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6
When we calculate the power for a number of different experimental designs, the calculations depend upon
A) a different approach to each kind of problem.
B) the way we use the tables.
C) the number of subjects we have.
D) the same basic steps, but with slightly different formulae.
A) a different approach to each kind of problem.
B) the way we use the tables.
C) the number of subjects we have.
D) the same basic steps, but with slightly different formulae.
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7
Power is most often conceived of as
A) a constant.
B) a variable.
C) a set of equations.
D) a probability.
A) a constant.
B) a variable.
C) a set of equations.
D) a probability.
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8
To increase power, the easiest variable to control in designing an experiment is usually
A) the difference between the population means.
B) the sample size.
C) the sample standard deviation.
D) the shape of the distribution.
A) the difference between the population means.
B) the sample size.
C) the sample standard deviation.
D) the shape of the distribution.
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9
Which of the following represents Cohen's rough estimates of small, medium, and large effect sizes?
A) .20, .50, .80
B) .00, .50, 1.50
C) .80, .50, .20
D) .40, .50, .60
A) .20, .50, .80
B) .00, .50, 1.50
C) .80, .50, .20
D) .40, .50, .60
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10
The probability of a Type II error is usually denoted by
A) beta (β).
B) alpha (α).
C) power.
D) the effect size ( g ).
A) beta (β).
B) alpha (α).
C) power.
D) the effect size ( g ).
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11
A Type II error is the probability of
A) finding a difference that is really there.
B) finding a difference that is not really there.
C) not finding a difference that is really there.
D) not finding a difference that is not really there.
A) finding a difference that is really there.
B) finding a difference that is not really there.
C) not finding a difference that is really there.
D) not finding a difference that is not really there.
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12
If we have two experiments in which the groups are equally different, the one with the larger power will be the one that
A) had the larger sample size.
B) had the smaller level of α.
C) had the larger β.
D) assigned subjects randomly.
A) had the larger sample size.
B) had the smaller level of α.
C) had the larger β.
D) assigned subjects randomly.
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13
The fact that the popular press can always find studies that failed to obtain the same findings as others suggests that
A) power is less than 1.00.
B) not all studies are equally clean.
C) there may be extraneous variables that are not being considered.
D) all of the above
A) power is less than 1.00.
B) not all studies are equally clean.
C) there may be extraneous variables that are not being considered.
D) all of the above
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14
Which of the following is involved in the calculation of power?
A) alpha (α)
B) the standard deviation
C) the difference between the means
D) All of the above are involved.
A) alpha (α)
B) the standard deviation
C) the difference between the means
D) All of the above are involved.
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15
When people such as Cohen say that a medium size difference has an effect size of .50, they are saying that we want the power for
A) one mean being half as large as another.
B) one mean being half a point larger than another.
C) one mean being half a standard deviation larger than another.
D) one mean being based on half as many subjects as the other.
A) one mean being half as large as another.
B) one mean being half a point larger than another.
C) one mean being half a standard deviation larger than another.
D) one mean being based on half as many subjects as the other.
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16
The effect size is generally denoted by
A) beta (β).
B) alpha (α).
C) d-hat (
).
D) delta (δ).
A) beta (β).
B) alpha (α).
C) d-hat (

D) delta (δ).
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17
When it comes to estimating the effect size we can use
A) prior research.
B) a statement of what we would expect to find.
C) special conventions that have been set by others.
D) all of the above
A) prior research.
B) a statement of what we would expect to find.
C) special conventions that have been set by others.
D) all of the above
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18
The effect size (
) is
A) the size of the difference between the means.
B) the size of the samples you use.
C) the difference between the means scaled by the size of the standard deviation.
D) the width of the distribution.

A) the size of the difference between the means.
B) the size of the samples you use.
C) the difference between the means scaled by the size of the standard deviation.
D) the width of the distribution.
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19
Knowledgeable and unbiased observers have generally noted, and studies have reliably shown, that psychotherapy is better than no treatment at all for a person who is seriously depressed. My study failed to find a difference. From this I can conclude that
A) psychotherapy really is not effective.
B) my study must have been poorly done.
C) my study may have lacked sufficient power to find a difference.
D) other psychologists don't know what they are talking about.
A) psychotherapy really is not effective.
B) my study must have been poorly done.
C) my study may have lacked sufficient power to find a difference.
D) other psychologists don't know what they are talking about.
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20
In the text the author complained about being asked "how many subjects do I need." His point was that this is a more complex question than it seems because you need to consider
A) how many subjects you have available.
B) how many subjects it would be convenient to run.
C) how many subjects your animal welfare committee will accept.
D) what the treatment effect is.
A) how many subjects you have available.
B) how many subjects it would be convenient to run.
C) how many subjects your animal welfare committee will accept.
D) what the treatment effect is.
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21
In calculating power we calculate a statistic called delta (δ). This statistic is
A) the effect size.
B) the sample size.
C) a combination of the effect size and the sample size.
D) the difference we are looking for.
A) the effect size.
B) the sample size.
C) a combination of the effect size and the sample size.
D) the difference we are looking for.
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22
Which of the following is a reason why we may NOT find a significant difference between two groups?
A) The sample size was too small.
B) The true mean difference between the groups was too small.
C) The variability between the groups was too large.
D) all of the above
A) The sample size was too small.
B) The true mean difference between the groups was too small.
C) The variability between the groups was too large.
D) all of the above
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23
Is it more meaningful to find a significant difference with a relatively small sample size or with a relatively large sample size?
A) It points to a more robust difference if you have a small sample size.
B) It points to a more substantial difference if you have a large sample size.
C) The two differences are equally substantial.
D) We can't tell anything about the size of the effect from what is given here.
A) It points to a more robust difference if you have a small sample size.
B) It points to a more substantial difference if you have a large sample size.
C) The two differences are equally substantial.
D) We can't tell anything about the size of the effect from what is given here.
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24
It is easy to forget whether the entry in the table at the back of the book represents power or 1 - power. (Different tables do it differently). We can easily figure it out, however. If the entry is power, we would expect
A) the values to decrease as we move down the table to larger sample sizes.
B) the values to decrease as we move across to higher levels of δ.
C) the values to increase as we move to the left to smaller α.
D) the values to increase as we move down the table to higher levels of δ.
A) the values to decrease as we move down the table to larger sample sizes.
B) the values to decrease as we move across to higher levels of δ.
C) the values to increase as we move to the left to smaller α.
D) the values to increase as we move down the table to higher levels of δ.
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25
The formula
allows us to calculate
A) the power for a t test for two independent samples.
B) the power for a t test for one sample.
C) the power for a test on a correlation coefficient.
D) any kind of power we need.

A) the power for a t test for two independent samples.
B) the power for a t test for one sample.
C) the power for a test on a correlation coefficient.
D) any kind of power we need.
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26
The text suggested that the highest value of power that we are likely to be able to afford, assuming that we don't have huge differences between our groups, is something like
A) .20
B) .50
C) .80
D) .95
A) .20
B) .50
C) .80
D) .95
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27
A harmonic mean can be used to calculate the mean sample size for unequal sample sizes. For _______ the values of k would equal _______.
A) related means t test; 3
B) related means t test; 2
C) independent samples t test; 3
D) independent samples t test; 2
A) related means t test; 3
B) related means t test; 2
C) independent samples t test; 3
D) independent samples t test; 2
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28
Power is controlled by
A) sample size.
B) variability.
C) true mean differences.
D) all of the above
A) sample size.
B) variability.
C) true mean differences.
D) all of the above
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29
If we have two related samples, the power of our test will
A) increase as the correlation between the two samples increases.
B) increase as the correlation between the two samples decreases.
C) be at its maximum when the correlation is zero.
D) The correlation is irrelevant.
A) increase as the correlation between the two samples increases.
B) increase as the correlation between the two samples decreases.
C) be at its maximum when the correlation is zero.
D) The correlation is irrelevant.
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30
If we have the possibility of different numbers of subjects in each of two groups, we will maximize our power if
A) we put most of the subjects in the group we care most about.
B) we put most of the subjects in the group we care least about.
C) we equalize the number of subjects in the two groups.
D) it doesn't make any difference so long as we maximize the total number of subjects overall.
A) we put most of the subjects in the group we care most about.
B) we put most of the subjects in the group we care least about.
C) we equalize the number of subjects in the two groups.
D) it doesn't make any difference so long as we maximize the total number of subjects overall.
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31
Which of the following reduces power?
A) large differences between the means
B) large levels of variability
C) large sample sizes
D) large alpha levels
A) large differences between the means
B) large levels of variability
C) large sample sizes
D) large alpha levels
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32
What is the power in an experiment with two independent groups when the null hypothesis is true?
A) .05
B) .95
C) .05/2
D) undefined
A) .05
B) .95
C) .05/2
D) undefined
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33
If we use the standard approach to solve for the necessary sample size so that we have power = .75 in a two-sample t test, the value of N that we will obtain from the tables is
A) the number of subjects we will need in each group.
B) the number of subjects we will need overall.
C) the number of groups we will need to run.
D) the number of subjects that we actually have available.
A) the number of subjects we will need in each group.
B) the number of subjects we will need overall.
C) the number of groups we will need to run.
D) the number of subjects that we actually have available.
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34
Do you have more power with a one-tailed test or a two-tailed test?
A) We have more power with a two-tailed test.
B) We have more power with a one-tailed test.
C) It depends on which alternative hypothesis is true.
D) Beats me!
A) We have more power with a two-tailed test.
B) We have more power with a one-tailed test.
C) It depends on which alternative hypothesis is true.
D) Beats me!
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35
In calculating power we separate the effect size and the sample size. We do this so that
A) we can look up the sample size needed for a specific effect size and power.
B) we can calculate the effect size we need for a given power.
C) we can avoid ever having to deal with the sample size.
D) we can confuse everyone.
A) we can look up the sample size needed for a specific effect size and power.
B) we can calculate the effect size we need for a given power.
C) we can avoid ever having to deal with the sample size.
D) we can confuse everyone.
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36
When we use the notation " f(N)" we are denoting
A) some function of the sample size.
B) a fraction of N .
C) the number of observations in the full sample.
D) the symbol for power.
A) some function of the sample size.
B) a fraction of N .
C) the number of observations in the full sample.
D) the symbol for power.
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37
Before running an experiment, we decide to calculate power. We find that the power equals .95. What conclusion can be made?
A) We should not run the experiment.
B) 95% of the time, we will not find a significant result.
C) We should run the experiment.
D) We need 95 subjects to find a significant result.
A) We should not run the experiment.
B) 95% of the time, we will not find a significant result.
C) We should run the experiment.
D) We need 95 subjects to find a significant result.
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38
It is important to think about power because
A) everyone uses it.
B) we don't want to run experiments that have little chance of finding something.
C) it is likely to guarantee successful studies.
D) none of the above
A) everyone uses it.
B) we don't want to run experiments that have little chance of finding something.
C) it is likely to guarantee successful studies.
D) none of the above
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39
Suppose a weak relationship exists between fetal alcohol syndrome and hyperactivity. We are more likely to find that the sample correlation is significant if
A) we have a small sample.
B) we have a very large sample.
C) it doesn't depend at all on sample size.
D) we choose people who have all experienced fetal alcohol syndrome.
A) we have a small sample.
B) we have a very large sample.
C) it doesn't depend at all on sample size.
D) we choose people who have all experienced fetal alcohol syndrome.
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40
When we have two independent groups with different numbers of subjects in the two groups, and we want to calculate the power we have for a given set of values of μ and σ, the N that we will use in our calculations is
A) the number of subjects in the smaller group.
B) the number of subjects in the larger group.
C) the harmonic mean of the two sample sizes.
D) the total number of subjects in our experiment.
A) the number of subjects in the smaller group.
B) the number of subjects in the larger group.
C) the harmonic mean of the two sample sizes.
D) the total number of subjects in our experiment.
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41
Power is the probability of correctly rejecting the null hypothesis.
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42
Power is defined as the
A) probability of rejecting a true null hypothesis.
B) probability of accepting a false null hypothesis.
C) probability of rejecting a false null hypothesis.
D) Power is not related directly to the null hypothesis.
A) probability of rejecting a true null hypothesis.
B) probability of accepting a false null hypothesis.
C) probability of rejecting a false null hypothesis.
D) Power is not related directly to the null hypothesis.
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43
According to statistical conventions, .80 is a small effect size.
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44
Power is higher when α is large than when α is small.
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45
The larger the true difference between two means, the smaller power is.
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46
Effect size is the difference between two population means divided by the sample size.
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47
The probability of rejecting a false null hypothesis is called
A) statistics.
B) power.
C) statistical significance.
D) prediction.
A) statistics.
B) power.
C) statistical significance.
D) prediction.
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48
Which of the following determines how the power of an experiment varies with sample size?
A) delta ( d )
B)
C) m 1 - m 2
D) Σ
A) delta ( d )
B)

C) m 1 - m 2
D) Σ
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49
If δ = 2.80, and α = .05, then power = .80.
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50
As sample size increases, so does power.
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51
We are trying to evaluate the efficacy of a treatment for claustrophobia. We have a control group that receives no treatment and an experimental group that receives our new treatment. We ask each participant to enter a very small room and stay there are long as they can. The mean of the control group is 10 seconds, with a standard deviation of 4 seconds. The mean of the experimental group is 18 seconds with a standard deviation of 8 seconds. Our best estimate of effect size is
A) 2.0
B) 1.33
C) 1.0
D) 1.75
A) 2.0
B) 1.33
C) 1.0
D) 1.75
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52
Suppose that in the previous question the 95% confidence interval on the difference between group means was computed to be 2.63 ≤ µ1 - µ2 ≤ 13.37. What can we conclude about the null hypothesis of no treatment effect?
A) The difference is significant.
B) The difference is not significant.
C) The treatment doesn't work.
D) Confidence intervals are totally unsuited to this question.
A) The difference is significant.
B) The difference is not significant.
C) The treatment doesn't work.
D) Confidence intervals are totally unsuited to this question.
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53
What is the easiest way to increase power?
A) redesign the study
B) decrease the error variance
C) use different statistical tests
D) increase the sample size
A) redesign the study
B) decrease the error variance
C) use different statistical tests
D) increase the sample size
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54
When we have two independent samples, the best measure of effect size
A) will use a pooled standard deviation.
B) might be based on the standard deviation of a control group.
C) both a and b
D) is best based on the standard deviation of the treatment group.
A) will use a pooled standard deviation.
B) might be based on the standard deviation of a control group.
C) both a and b
D) is best based on the standard deviation of the treatment group.
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55
If power = .75, there is a 25% chance of correctly rejecting the null hypothesis.
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56
When effect size is small, a small sample is typically sufficient to identify important differences.
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57
When we have two independent samples, a confidence limit is generally used to
A) say something about the difference between population means.
B) say something about the difference between sample means.
C) specify the location of a single sample mean.
D) refine the estimate of the variance.
A) say something about the difference between population means.
B) say something about the difference between sample means.
C) specify the location of a single sample mean.
D) refine the estimate of the variance.
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58
In computing effect sizes for a comparison of independent samples, our measure may be less than ideal if
A) we have heterogeneous variances and no control group.
B) the data are decidedly nonnormal.
C) we choose the wrong statistic for our denominator.
D) all of the above
A) we have heterogeneous variances and no control group.
B) the data are decidedly nonnormal.
C) we choose the wrong statistic for our denominator.
D) all of the above
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59
When comparing independent means, power is greater when sample sizes differ substantially.
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60
You are on an Institutional Animal Care and Use Committee (IACUC) at your school. You receive a request to run an animal study where the power will be .40. Do you approve the study?
A) Yes; this indicates the study has a 60% chance of obtaining a significant result
B) No; this indicates the study has only a 40% chance of obtaining a significant result.
C) Yes; this indicates the results will be incorrect only 40% of the time.
D) No; this indicates the study has a 40% chance of missing the significant result.
A) Yes; this indicates the study has a 60% chance of obtaining a significant result
B) No; this indicates the study has only a 40% chance of obtaining a significant result.
C) Yes; this indicates the results will be incorrect only 40% of the time.
D) No; this indicates the study has a 40% chance of missing the significant result.
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61
Given the following values for δ, what is power assuming α = .05?
a. δ = 1.55
b. δ = 3.60
c. δ = 2.65
a. δ = 1.55
b. δ = 3.60
c. δ = 2.65
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62
A clinician is interested in examining the effectiveness of a new treatment approach for depression. Currently, 20 people are in the control group and 20 people are in the intervention group. In similar research, clinicians have reported post-treatment depression scores of 30 and 26 for the control groups and intervention groups respectively, and a standard deviation of 4.5. What is a reasonable estimate of power if α = .05?
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63
In a related samples t-test, husbands and wives scores are correlated such that r = .55, and the typical standard deviation on the measure of marital satisfaction is 5. Assuming the true mean difference in marital satisfaction is 5 points, the sample consists of 10 couples, and α = .05:
a. What is
?
b. What is δ?
c. What is power?
a. What is

b. What is δ?
c. What is power?
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64
A student preparing to use a one-sample t-test indicated that power = .80 with a sample of 30. What was the effect size assuming α = .05?
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65
The effect size for a one-sample t-test is .45. How many subjects would be necessary for the following levels of power if α = .05?
a. .40
b. .80
c. .95
a. .40
b. .80
c. .95
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66
A pediatrician is interested in determining if cognitive development scores are lower for low-birthweight infants than normal infants. She has 49 active cases involving low-birthweight infants from who she could collect data to compare to the national average. What would power be assuming the following effect sizes and α = .05?
a.
=.20
b.
=.50
c.
=.80
a.

b.

c.

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67
Calculate effect size given the following information:
a. μ 1 =30, μ 2 = 35, σ = 3
b. μ 1 =40, μ 2 = 30, σ =10
c. μ 1=100, μ 2 = 98, σ = 5
a. μ 1 =30, μ 2 = 35, σ = 3
b. μ 1 =40, μ 2 = 30, σ =10
c. μ 1=100, μ 2 = 98, σ = 5
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68
The effect size for an independent samples t-test is .90. How many subjects would be necessary for the following levels of power if α = .05?
a. .50
b. .77
c. .91
a. .50
b. .77
c. .91
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69
An English teacher believes his method of teaching grammar, usage, and mechanics is superior to most other approaches. He plans to compare his students' average score on a standardized test to the national average. Assuming a medium effect size, 20 students in his class, and α = .05, what is power?
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70
Identify and explain three factors that affect power.
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