Q&A Hero

Q: 1+ A factorial analysis of variance has a) more than one dependent variable. b) more than one independent variable. c) every level of every independent variable paired with every level of every other independent variable. d) both b and c

Q: 78 A researcher noted that there was a significant interaction effect of amount of time studying and hours of sleep the night before an exam on exam scores. He calculated simple effects to try to interpret the data. Here are the results. Graph them and explain the nature of the interaction. Study 2 or more hours Study less than 2 hours t6 or more hours of sleep 83 75 2.65*Less than 6 hours of sleep 76 74 1.35df = 30; *p < .05

Q: 77 Calculate and explainfor treatment group from the previous problem.

Q: 76 Calculate and interpret F for each effect based on the following data.Source SS dfTreatment group 1700.50 4Problem severity 1144.57 2Treatment X Severity 3008.504 8Error 30412.86 186Total 36266.434 200

Q: 75 Calculate and explain 2 for the significant effects from the previous data.

Q: 74 a) How many levels are there for each factor? b) Which effects are statistically significant?

Q: 73 Plot the data from the previous question three times (each main effect and the interaction effect); interpret the graphs.A human resources director for a large company wanted to compare salaries based on minority status and the type of job. Answer the following questions based on the following SPSS output.

Q: 72 A doctor examining the effectiveness of smoking cessation programs wanted to examine the independent and joint effect of a support group and the patch. The following data are the average number of packs smoked 2 weeks after the interventions. Each group consisted of 10 people. Answer the following questions based on this table of means. Using Patch Not using patchIn support group 0 2.5Not in support group 1.5 3.0a) What is the grand mean?b) Calculate the mean packs smoked at each level of support group.c) Calculate the mean packs smokes at each level of the patch.

Q: 71 In the previous example,a) how many treatment groups were being compared?b) what was N?c) how many cells are there in the design?

Q: 70 Determine whether each of the following effects is statistically significant at  = .05.Source df FGender 1 2.56Treatment 3 2.75Gender X Treatment 3 3.26Error 120 Total 127

Q: 69 What value appears in each identified cell in the following table? Fall Winter SpringClassroom A 10 15 16Classroom B 12 12 14Classroom C 8 10 12Classroom D 10 12 10a) X11b) X23c) X41

Q: 68 In analysis of variance, factor refers to independent variables.

Q: 67 Three main effects and three interactions are tested in a factorial design with three independent variables.

Q: 66 In a factorial design based on two independent variables, three F values will be calculated.

Q: 65 X13 refers to the value located in the first row and the third column.

Q: 64 The mean difference in GPA based on Gender for Freshman only is a simple effect.

Q: 85 Calculatet using Fisher's Least Significance Difference test to determine which groups are significantly different from one another in the previous example.

Q: 84 Based on the following data, create an ANOVA summary table and calculate and interpret F.GROUP DELAY1 .501 .751 1.001 1.251 1.002 1.002 2.002 3.002 1.002 3.003 1.003 .753 .503 .503 1.25

Q: 83 Given the following information, what are the degrees of freedom for the numerator and the denominator. a) k = 5, N = 400 b) k = 3, N = 75 c) k = 4, N = 98

Q: 82 Calculate and for the previous problem.

Q: 81 Answer the following questions based on this SPSS output.a) How many groups were compared?b) What was the total sample size?c) Was the ANOVA significant?d) Which groups are significantly different from one another? Explain the nature of the differences.

Q: 80 An overall ANOVA was significant. A student calculated t-tests between each of the groups. Each group consisted of 15 people. Which groups are significantly different from one another using a Bonferroni correction? Groups being compared 1 & 2 1 & 3 1 & 4 2 & 3 2 & 4 3 & 4t value 5.63 3.56 4.29 2.60 1.79 2.76

Q: 79 Calculate 2 and for the previous problem.

Q: 78 Given the following information, calculate and interpret F.Source df SSGroup 3 312.63Error 50 560.76Total 53 873.39

Q: 77 Indicate whether or not each of the following F statistics are significant based on the following information, assuming  = .05. a) F (4, 120) = 3.26 b) F (2, 60) = 3.10 c) F (6, 500) = 2.14

Q: 76 Name 3 assumptions underlying a one-way ANOVA.

Q: 75 If 2 = .16, 4% of the variability in the dependent variable is attributable to group membership.

Q: 74 In a Bonferrroni procedure, is divided by the number of groups.

Q: 73 dfgroup is the number of groups being compared in the ANOVA.

Q: 72 The grand mean is the mean of all observations across all groups.

Q: 71 The larger the ratio of the more likely that the group means differ significantly one another significantly.

Q: 70 F is the ratio of MSgroup divided by MSerror.

Q: 69 MSgroup is the variability among subjects in the same group.

Q: 68 MSerror is the variability among group means.

Q: 67 An ANOVA is used to compare the means of two or more groups.

Q: 66 Which of the following represents a measure of the magnitude of effect?

Q: 65 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: 64 We generally don"t compute a confidence interval on the omnibus null hypothesis because a) it is not clear what it would mean if we could do so. b) we don"t know how to do so. c) it does not address the questions we are likely to want to answer. d) all of the above

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