Q&A Hero

Q: 63 When we use the phrase "omnibus null hypothesis" we are referring to a) b) c) d)

Q: 62 Cohen's is generally a better measure than 2 or ·2 becausea) it is more specific to individual treatments.b) it is less biased than any other measure.c) it pulls together information from all of the treatments.d) It actually is a worse measure than the others.

Q: 61 We have run a one-way ANOVA comparing three treatments for anorexia and found a significant difference. We now want to convey the most useful information to our reader about how effect one treatment is relative to one or more other treatments. The best statistic to use here to convey that information would most likely be

Q: 60 When we run a one-way ANOVA with four groups and obtain a significant F, the best effect-size measure to convey what that result tells us is

Q: 59 What are our choices for effect size measures for a one-way ANOVA?

Q: 58 A common criticism of Fisher's LSD test is that a) it is sometimes too conservative. b) it is sometimes too liberal. c) it is too difficult. d) it relies on a non-normal distribution.

Q: 57 The post-hoc test which holds the familywise error rate at .05 by running each individual test at the c/alpha level (# comparisons/alpha) is the a) Fisher's LSD. b) Bonferroni. c) Newmann Keuls. d) Tukey test.

Q: 56 In multiple comparison procedures, post-hoc tests are completed after the ANOVA. Why are post-hoc tests preferred over running several t-tests? a) They decrease the probability of a Type I error. b) They do not control familywise error rate. c) It increases the probability of a Type I error. d) They are more likely to be significant.

Q: 55 The book discusses an experiment by Merrell that examined the effects of Anthrax, Mozart, and no music on the amount of time it took a mouse to run a maze. To determine if there is an overall difference between the three groups, Merrell ran an ANOVA. To determine which means differed for each other, he ran a a) regression. b) repeated-measures t-test. c) Bonferroni test. d) chi-square.

Q: 54 A student wanted to determine if the mean number of times a student missed class was different for sophomores, juniors, and seniors. After collecting attendance data, the student ran an ANOVA and found that MSgroups was much larger than MSerror. This student can conclude that a) sophomores miss class more than juniors and seniors. b) there is a difference in the mean number of times sophomores, juniors, and seniors miss class. c) seniors miss class more than sophomores and juniors. d) there is no difference between the groups.

Q: 53 You want to control the _______ when multiple comparisons are being made? a) probability error rate b) significance error rate c) familywise error rate d) test-retest error rate

Q: 52 When analyzing results of an ANOVA we are most interested in the _______. a) F Statistic b) t Statistic c) R Squared d) both a and c

Q: 51 What type of multiple comparison procedure should be used if we want to divide the familywise error rate among the number of comparisons that we are performing? a) Fisher's LSD b) Bonferroni procedure c) factorial ANOVA d) paired samples t-test

Q: 50 The mean square error (MSerror) is a measure of a) how different the group means are. b) whether the dependent variable was measured incorrectly. c) how much variability there is within each group. d) whether the ANOVA is significant.

Q: 49 We want to compare the scores of different groups on a measure of reaction time. Three different groups were studied: patients with recent head injuries, patients with head injuries that occurred a year ago, and a control group of non-injured people. We want to know which group of people has the fastest reaction time. What is the best statistical test to use to find this out? a) one way ANOVA b) factorial ANOVA c) paired samples t-test d) correlation

Q: 48 The familywise error rate is a) the probability of at least one Type I error in a set of comparisons. b) the probability of no Type I errors. c) the number of Type I errors that you are likely to make. d) the probability of a Type II error.

Q: 47 When looking at multiple comparisons, the more tests that you run, the more likely that you will have a _______. a) Type I error b) Type II error c) mean squared error d) random error

Q: 46 In the analysis of variance, MSGroups measures how different group means are, and MSerror measures variability within each group. If the null hypothesis were false, what would we expect to find? a) That MSgroups and MSerror would be roughly equal. b) That MSgroups would be larger than MSerror. c) That MSerror is larger than MSgroups. d) That MSerror is close to zero.

Q: 45 We want to compare the scores of different groups on a measure of reaction time. Three different groups were studied: patients with recent head injuries, patients with old head injuries, and a control group of non-injured people. We want to know which group of people has the fastest reaction time. What is the best statistical test to use to find this out? a) one-way ANOVA b) factorial ANOVA c) paired samples t-test d) correlation

Q: 44 Eysenck's study on recall as a function of level of processing showed a) processing makes only minimal difference to recall. b) old people don"t learn anything. c) just telling someone to learn a list of words doesn"t work. d) recall increases with the level of processing.

Q: 43 Which of the following is not a multiple comparison procedure we have discussed in class or seen in the texts. a) Fisher's LSD test. b) The Stroop test. c) The Bonferroni test. d) The Newman-Keuls test.

Q: 42 The null hypothesis behind a simple multiple-group analysis of variance is of the form: a) b) c) d)

Q: 41+ A researcher found significant differences in the mean running speeds of sprinters wearing shoes made by Nike, Reebok, and Adidas using an analysis of variance. The 2 calculated on the basis of group membership (based on which shoes were worn) equaled .16. The value of 2 shows thata) the r value would be .4.b) 84% of the variability in running speed is attributed to shoe brand.c) 16% of the variability in running speed is attributed to shoe brand.d) most of the factors influencing running speed are contained in the brand of shoes worn by runners.

Q: 40 The magnitude of effect in a study was calculated to yield values for both 2 and 2. Which of the following relationships between 2 and 2 is likely?a) 2 = 2b) 2 > 2c) 2 < 2d) none of the above

Q: 39 The major difference between 2 (eta-squared) and 2 (omega-squared) is thata) 2 tends to overestimate the true value in the population.b) 2 tends to overestimate the true value in the population.c) calculation of 2 uses the number of groups.d) the calculation of 2 is quicker and easier.

Q: 38 We can probably get away with violating assumptions if a) the data are reasonably normal. b) the variances are not too different. c) the unequal variances are not paired with very unequal ns. d) all of the above

Q: 37 The Bonferroni procedure controls error rates bya) operating at a reduced level of b) operating at an increased level of c) not allowing you to make any comparisons unless the F is significant.d) changing the error term.

Q: 36 The familywise error rate is a) the probability of at least one Type I error. b) the probability of no Type I errors. c) the number of Type I errors that you are likely to make. d) the probability of a Type II error.

Q: 35+ Fisher's LSD test is most useful when a) you have only two means. b) you have two or three means. c) you have many means. d) you have a nonsignificant overall F.

Q: 34+ If we run six independent comparisons among means, each at the five percent level, the overall familywise error rate will be approximately a) .05. b) .05/6. c) .30. d) .01.

Q: 33 Which of the following is a possible null hypothesis in an analysis of variance with 5 groups?a) the first oneb) the second onec) both the first and secondd) Neither of these is a null hypothesis.

Q: SourcedfSSMSFpGroup2226.932113.4665.53.031Error91845.99320.511 Total922072.925 In the experiment whose summary table is given above, the average standard deviation in each of the groups was approximatelya) 110.b) 20.c) 4.5.d) 92.

Q: SourcedfSSMSFpGroup2226.932113.4665.53.031Error91845.99320.511 Total922072.925 What would you conclude from the summary table above?a) The difference "between groups" is significant by a one-tailed test of b) The difference "between groups" is not significant.c) The difference "between groups" is significant.d) We don"t have enough information to draw a conclusion.

Q: SourcedfSSMSFpGroup2226.932113.4665.53.031Error91845.99320.511 Total922072.925 How many groups were there in this experiment?a) 1b) 2c) 3d) 4

Q: SourcedfSSMSFpGroup2226.932113.4665.53.031Error91845.99320.511 Total922072.925 How many subjects were there in this experiment?a) 100b) 95c) 93d) 92

Q: 28+ Unequal sample sizes in a one-way analysis of variance are generally a) a major problem. b) a minor inconvenience. c) something to be avoided at all costs. d) impossible.

Q: 27 In a one-way analysis of variance we deal with unequal sample sizes by a) not allowing them. b) doing nothing different. c) averaging the means. d) multiplying each squared deviation by nj as we go along.

Q: 26 For an F value to be significant it must a) be positive. b) equal 1.0. c) exceed the tabled value. d) be less than the tabled value.

Q: 25 Mean squares are closest to a) means. b) variances. c) standard deviations. d) Fs.

Q: 24 The column of mean squares in the analysis of variance is obtained by a) dividing the sums of squares by the degrees of freedom. b) multiplying the degrees of freedom times the sums of squares. c) dividing the sum of squares for treatments by the sum of squares for error. d) dividing the degrees of freedom by each other.

Q: 23 In an analysis of variance summary table, the df for groups always equals a) the number of groups. b) the number of groups minus one. c) the number of subjects per group. d) the total number of subjects minus one.

Q: 22 The notation is used to calculate a) SSbetween b) SSwithin c) SStotal d) MSerror

Q: 21 The notation produces the term we call thea) SSbetweenb) SSwithinc) SStotald) MSerror

Q: 20+ When we reject the null hypothesis in the analysis of variance we can conclude that a) all of the means are the same. b) all of the means are different. c) at least one of the means is different from at least one other mean. d) only one mean is different from one other mean.

Q: 19 If the null hypothesis in the analysis of variance were true, a) the variances would all be the same. b) the sample means would all be the same. c) the population means would all be the same. d) every subject would have the same score.

Q: 18 We use the symbol to represent a) the variance of the individual observations. b) the variance of the group totals. c) the variance of the error scores. d) the variance of the means.

Q: 17 When we use the phrase "within group" we mean a) the variability of the group means. b) the variability within the group means. c) the variability calculated for the scores within each group separately. d) the variability within all of the data points.

Q: 16 In the analysis of variance, MSerror is a) the average of the between group variances. b) the average of the between group sums of squares. c) the sum of squares of the within group variances. d) the average of the within group variances.

Q: 15+ In evaluating the F in the analysis of variance, we need to know a) the degrees of freedom for the Between Groups term. b) the degrees of freedom for the Within Groups term. c) only the total number of degrees of freedom. d) both a and b

Q: 14+ In the analysis of variance, the more the null hypothesis is false, a) the larger the value of F. b) the smaller the value of F. c) the smaller the value of the correlation coefficient. d) the harder it is to find a significant difference.

Q: 13 If the null hypothesis is true, we would expect the F in the analysis of variance to be a) approximately 0. b) somewhere around 1. c) at least 10. d) the value of F is not dependent on the status of the null hypothesis.

Q: 12+ The analysis of variance compares a) the total variance with the variance within groups. b) the total variance with the variance between group means. c) the variance between group means with the variance within groups. d) the variance within groups with the variance among all data points.

Q: 11+ When we speak about error variance in the analysis of variance we are speaking of a) differences between subjects in the same group. b) differences between subjects in different groups. c) the overall variability of scores in the experiment. d) the misrecording of data.

Q: 10 An important assumption in the one-way analysis of variance is that a) observations are random. b) observations are independent. c) subjects are related. d) there are equal numbers of observations in each group.

Q: 9 The analysis of variance assumes that a) the populations have no variance. b) the samples have equal variances. c) the populations have equal variances. d) the variances are normally distributed.

Q: 8 In the analysis of variance we will assume that a) the populations are normally distributed. b) the populations follow a rectangular distribution. c) the populations all have completely different shapes. d) There is no assumption about the shape of the population.

Q: 7+ If we had the following pattern of population means we would hope to conclude thata) the null hypothesis is false.b) the null hypothesis is true.c) the null hypothesis is confused.d) the experiment will have very little power.

Q: 6 If we want to have faith in the results of our particular study, we will be most concerned with a) random sampling. b) random assignment. c) equal sample sizes. d) a significant F.

Q: 5 Which of the following is not a critical element of the analysis of variance? a) the variance within each group b) the variance of the means c) the variance of the total sample d) the difference between the means

Q: 4 In the analysis of variance with three groups the null hypothesis is a) the three population means are all different. b) at least one of the population means is different from the others. c) the three population means are equal to each other. d) We can"t tell from what is given here.

Q: 3 In the Eysenck study of recall of lists of words, a significant F in the analysis of variance would at the least tell us that a) greater processing leads to greater recall. b) less processing leads to greater recall. c) the recall means are different in the different groups. d) none of the above

Q: 2 The major difference between t tests and the analysis of variance is that the latter a) deals with multiple groups. b) compares group variances. c) makes different assumptions about the populations from which we sample. d) none of the above

Q: 1+ The analysis of variance differs from a t test for two independent samples because a) thet test is limited to 2 samples. b) the analysis of variance can handle multiple samples. c) they test different hypotheses. d) both a and b

Q: 70 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 = .05, what is power?

Q: 69 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 = .05?

Q: 68 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 = .05:

Q: 67 The effect size for a one-sample t-test is .45. How many subjects would be necessary for the following levels of power if = .05?a) .40b) .80c) .95

Q: 66 The effect size for an independent samples t-test is .90. How many subjects would be necessary for the following levels of power if = .05?a) .50b) .77c) .91

Q: 65 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 = .05?

Q: 64 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 = .05?

Q: 63 Calculate effect size given the following information: a) = 3 b) = 10 c) = 5

Q: 62 Given the following values for , what is power assuming = .05?

Q: 61 Identify and explain three factors that affect power.

Q: 60 When comparing independent means, power is greater when sample sizes differ substantially.

Q: 59 When effect size is small, a small sample is typically sufficient to identify important differences.

Q:

Q: 57 If power = .75, there is a 25% chance of correctly rejecting the null hypothesis.

Q: 56 According to statistical conventions, .80 is a small effect size.

Q: 55 Effect size is the difference between two population means divided by the sample size.

Q: 54 Power is higher when  is large than when  is small.