Q&A Hero

Q: 53 As sample size increases, so does power.

Q: 52 The larger the true difference between two means, the smaller power is.

Q: 51 Power is the probability of correctly rejecting the null hypothesis.

Q: 50 Suppose that in the previous question the 95% confidence interval on the difference between group means was computed to be . 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.

Q: 49 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

Q: 48 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.

Q: 47 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

Q: 46 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.

Q: 45 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.

Q: 44 Which of the following determines how the power of an experiment varies with sample size?

Q: 43 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

Q: 42 The probability of rejecting a false null hypothesis is called a) statistics. b) power. c) statistical significance. d) prediction.

Q: 41 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.

Q: 40 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

Q: 39 Power is controlled by a) sample size. b) variability. c) true mean differences. d) all of the above

Q: 38 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.

Q: 37 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

Q: 36 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.

Q: 35+ 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

Q: 34+ 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

Q: 33+ 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

Q: 32 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!

Q: 31 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.

Q: 30 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 expecta) 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 .c) the values to increase as we move to the left to smaller .d) the values to increase as we move down the table to higher levels of .

Q: 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.

Q: 28 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.

Q: 27 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 and , the N that we will use in our calculations isa) 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.

Q: 26+ 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.

Q: 25+ 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

Q: 24 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.

Q: 23 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.

Q: 22 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.

Q: 21+ In calculating power we calculate a statistic called delta (). 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.

Q: 20 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

Q: 19+ 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.

Q: 18 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

Q: 17+ 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.

Q: 16+ The effect size is generally denoted by

Q: 15 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.

Q: 14+ 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.

Q: 13 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.

Q: 12+ If we have two experiments in which the groups are equally different, the one with the larger power will be the one thata) had the larger sample size.b) had the smaller level of .c) had the larger d) assigned subjects randomly.

Q: 11 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.

Q: 10+ Which of the following is involved in the calculation of power?a) alpha ()b) the standard deviationc) the difference between the meansd) All of the above are involved.

Q: 9 Power is most often conceived of as a) a constant. b) a variable. c) a set of equations. d) a probability.

Q: 8 The probability of a Type II error is usually denoted by

Q: 7 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.

Q: 6+ 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

Q: 5 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.

Q: 4 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

Q: 3 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

Q: 2+ 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

Q: 1 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.

Q: 25 When we say that two independent variables, such as gender and age, are confounded, we mean that a) one variable blocks the influence of the other. b) we cannot completely tell the effect of gender apart from the effect of age. c) we cannot do anything with the study. d) the data were collected carelessly.

Q: 24+ For a very conservative test when we don"t pool the variances we shoulda) work at = .01 instead of = .05.b) insist that the critical value of t be twice the tabled value.c) use a much reduced number of degrees of freedom.d) throw up our hands and call the problem too difficult.

Q: 23 When we have very unequal sample variances, we should a) check our work very carefully when we pool the variances. b) not pool the variances. c) average the variances, but not weight them with the degrees of freedom. d) run some different analysis.

Q: 22+ In the previous test on the treatment of anorexia, the resulting t was "3.22, which was significant (p < .05). This tells us that a) the family therapy condition had a mean that was reliably less than the mean of the control condition. b) the family therapy condition had a mean that was reliably more than the mean of the control condition. c) the family therapy condition had a mean that was unreliably less than the mean of the control condition. d) the family therapy condition had a mean that was unreliably more than the mean of the control condition.

Q: 21+ If we reject the null hypothesis with a two-tailed test in the previous anorexia condition, we would side with which of the following alternatives?

Q: 20 In the anorexia example comparing Family Therapy and Control conditions the null hypothesis would be

Q: 19 In the previous example, how many df do we have? a) 25 b) 43 c) 41 d) 21.5

Q: 18+ The following data are taken from Chapter 14 and refer to a study of weight gain in treated and untreated girls suffering from anorexia. untreated treated Mean -0.45 7.26 St Dev. 7.99 7.16 Variance 63.82 51.23 N 26 17 Which of the following formula for t in this situation would be a correct one? a) b) c) d) .

Q: 17 When we have an independent sample t test, the degrees of freedom are equal toa) Nb) N1 + N2 - 1c) N1 + N2 - 2d) N - 1

Q: 16 Which of the following formulae for t is correct? a) b) c) d) all of the above

Q: 15+ A weighted average is a) the average of two weights. b) an average that gives greater influence to the larger sample. c) an average that reduces the influence of the larger sample. d) the balance between the sample size and the mean.

Q: 14 Our assumption that population variances are equal is called the assumption of a) equal dispersion. b) heterogeneity of variance. c) homogeneity of variance. d) pooled variances.

Q: 13 The reason that we pool variances is to a) inflate our error term. b) get a better estimate of error variance. c) reduce the sample variance. d) increase the size of t.

Q: 12 We would NOT pool the variances if a) we had too few subjects. b) we had too many subjects. c) The means were clearly different. d) we had very unequal sample variances.

Q: 11+ When we speak about pooling variances we are referring to a) averaging the two groups' variances. b) using the variance of the larger group. c) adding up the variances in each of two groups and dividing by 2. d) taking the variance of both sets of data combined.

Q: 10 To go from the equation in the previous problem to the equation for t we must a) substitute sample means for population means. b) substitute sample variances for population variances. c) substitute sample standard deviations for population variances. d) draw very large samples.

Q: 9 Given the following equation, the only difference between this and our original equation for z is: a) the original z required a normal distribution. b) we have substituted information about differences in place of information about observations. c) the equations are of the same general form. d) both b) and c).

Q: 8 Thet statistic differs from z in that a) it applies to variances. b) it is used when population variances are not known. c) it involves an assumption of normality. d) and b) but not c).

Q: 7 When variables A and B are independent, the variance of A - B is equal to a) the variance of A plus the variance of B. b) the variance of A. c) variance of A minus the variance of B. d) it cannot be determined from the information given here.

Q: 6 The variance sum law deals with a) the variance of the sum of two or more variables. b) the variance of the difference of two or more variables. c) the variance of any single variable. d) both a) and b).

Q: 5 The distribution of differences between means is a) normally distributed for very large samples. b) approaches normal as sample sizes increase. c) may be nonnormal for small samples. d) all of the above.

Q: 4+ When testing the means of independent samples, the null hypothesis is best thought of as a) the mean of population 1 is equal to the mean of population 2. b) the mean of population 1 is unequal to the mean of population 2. c) the mean of a set of difference scores is equal to 0. d) the two population means don"t differ by more than 10 points.

Q: 3 Which of the following would make you believe that you have two independent groups? a) Subjects were assigned to groups at random as they arrived for testing. b) There are 25 subjects in Group 1 and 45 subjects in Group 2. c) Every subject supplies one score. d) All of the above.

Q: 2+ Which of the following would most likely NOT be independent samples? a) Group 1 contains wives and Group 2 contains their husbands. b) Group 1 contains women and Group 2 contains men. c) Group 1 contains dyslexic children and Group 2 contains non-dyslexic children. d) Group 1 contains smokers and Group 2 contains nonsmokers.

Q: 1+ The most important characteristic of two independent samples is a) we measure the same subjects on two separate times. b) the subjects in one sample are part of the same family as subjects in the other sample. c) the set of scores for one sample is uncorrelated with the scores in the other sample. d) the subjects in a group are people who know each other.

Q: 63 A movie critic believes people linger in the theatre after a movie for longer periods following dramas than comedies. The data follow. Dramas Comedies 100 sec 90 secs2 35 sec 8 secN 50 150a) What is the research hypothesis?b) Is a one-tail or a two-tail test more appropriate?c) Calculate t.d) Is the research hypothesis supported? Explain

Q: 62 Refer to the following output to answer these questions.a) Has the assumption of homogeneity of variance been met?b) Which t-test should be used to interpret the data?c) Write a sentence summarizing the results of the t-test.