Q&A Hero

Q: 18+ The assumptions behind the analysis of repeated-measures designs include a) the assumption that all levels of the repeated measure are equally correlated with each other. b) the assumption of normality. c) the assumption of homogeneity of variance. d) all of the above

Q: 17 In running multiple comparisons in a repeated-measures design we can use procedures that we would use with independent groups designs because a) the error term is corrected for any lack of independence in the data. b) the error term is a conservative one. c) the multiple comparison procedures we use have nothing to do with the question of independence or lack of it. d) we create our own adjusted error term for multiple comparisons.

Q: 16+ If we compared Time 1 (baseline) against the next time (Time 2) and then against the last time (follow-up), we would run the Bonferroni at

Q: 15 If we used a Bonferroni test to run multiple comparisons in the above example, the error term that we would use would be a) the multiple comparison adjusted error term. b) the MSerror from the table above. c) the MSsubjects term. d) MSerror/5.

Q: 14 If we wanted to run a set of multiple comparisons on the data analyzed in the summary table above, we could use a) Fisher's LSD test. b) the Repeated-Measures MC test. c) the Bonferroni t test. d) both a and c

Q: 13 The error term in this analysis could also be thought of asa) the within cells term.b) the between cells term.c) the Subject x Trials interaction.d) the variance.

Q: 12+ How many trials were there in this experiment? a) 2 b) 4 c) 5 d) 8

Q: 11+ The results of this study tell us that a) there is a change over trials. b) there is no change over trials. c) subjects are different. d) There is too much noise in the system to draw any conclusions.

Q: 10 The MSerror = 30.68 tells us that a) the average variance in this study is 30.68 units. b) the average variance within the set of scores for a given subject is 30.68 units. c) the average difference due to time is 30.68 units. d) We cannot tell from what is given.

Q: 9+ We don"t have an F test on Subjects. What harm does that do? a) It diminishes the value of the study. b) It distorts the meaning of a significant trials effect. c) It alters SStotal. d) It does no particular harm.

Q: 8+ How much has the error sums of squares been reduced over what it would have been in a comparable between-subjects design? a) It has not been reduced at all. b) 30.68 units c) 723.5 units d) 1687.3 units

Q: 7+ How many subjects were involved in this study? a) 14 b) 15 c) 74 d) 75

Q: 6 If, in the example of a headache study used in the text, all subjects had been studied over the same period of time, differences that might be caused by stressful times (such as Christmas) woulda) contaminate the results.b) add to the usefulness of the results.c) improve the generalizability of the study.d) reduce the variability in the scores.The next few questions are based on the following summary table. SourcedfSSMSFSubjects14723.5 Trials41687.3421.8213.74*Error561718.530.68 Total744129.3 *p<.05

Q: 5 If we have a repeated-measures design with subjects receiving four levels of a treatment, we assume that a) the correlations among the levels will be zero. b) the correlations among the levels will be 1.0 c) the correlations among the levels will be random. d) the correlations among the levels will all be about the same.

Q: 4 For repeated-measures designs with one independent variable (Time), a) subjects served under all levels of the independent variable. b) subjects served under only some of the levels of the independent variable. c) subjects served under only one level of the independent variable. d) none of the above

Q: 3 All other things being equal, a repeated-measures design is _______ than the corresponding between-subjects design. a) less powerful. b) more powerful. c) The two designs have comparable power. d) We cannot predict this.

Q: 2+ All other things equal, the MSerror in a repeated-measures design is _______ than the corresponding MSerror in a between-subjects design. a) smaller. b) larger c) the same size. d) We have no way to predict this.

Q: 1+ A repeated-measures analysis of variance differs from a one-way and a factorial design because a) the measures in a repeated-measures design are correlated. b) the measures in a standard factorial are independent. c) the measures in a repeated-measures design are not independent from time to time. d) all of the above

Q: 63 The mean difference in GPA based on gender and year in school is a main effect.

Q: 62 The mean difference in GPA based on gender is an interaction effect.

Q: 61 A 2 X 4 factorial involves two independent variables. One has two levels and the other has four.

Q: 60 A factorial analysis of variance involves more than one dependent variable.

Q: 59 To calculate the F for a simple effect you a) use the mean square for the main effect as the denominator in F. b) first divide the mean square for the simple effect by its degrees of freedom. c) use the same error term you use for main effects. d) none of the above

Q: 58 Using the example in the text of a participant receiving therapy while sitting in a bath of ice water, what would be the best denominator for calculating ? a) the square root of MSerror b) the square root of MSerror after removing effects due to the Ice condition and its interaction with treatment c) the standard deviation of participants in the non-ice condition d) the standard deviation of difference scores

Q: 57 When we say that a measure is "not of theoretical interest" we mean that a) variability attributable to it should be removed from the denominator. b) we can simply ignore that variable. c) variability attributable to it should be included in the denominator. d) there is no significant effect for that variable.

Q: 56 When we compute an effect size measure such as for a factorial ANOVA we have to decide a) what effects should be included in estimating the denominator. b) what are our variables of theoretical interest. c) whether we want an r-family measure or a d-family measure. d) all of the above

Q: 55 What type of design is the above study? a) 2 x 2 x 2 b) 2 x 2 c) 2 x 3 d) 3 x 3 x 3

Q: 54 In the Spilich et al. study of the effects of smoking that was discussed in the text, active smokers were found to do better than nonsmokers on a driving task but did worse than nonsmokers on a cognitive task. However, over all three tasks (the third was pattern recognition and the groups were not different on that) active smokers did not differ from nonsmokers on performance. The results suggest a) an interaction between smoke group and task, and a main effect for smoke group. b) an interaction between smoke group and task, but no main effect for smoke group. c) a main effect for smoke group, but no interaction between smoke group and task. d) a main effect for task only.

Q: 53 Dr. Gates looked at the effects of frustration on the use of profanity by males and females. Males and females were asked to write a lab report on computers in a lab, but half the computers were set up to crash during the session while half of the computers were not set up to crash. Three observers recorded the use of profanity by the participants during the task. What is the design of this study? a) 2 x 2 factorial b) 1 x 2 factorial c) 2 x 2 x 3 factorial d) 2 x 2 correlational

Q: 52 The overall effect of an independent variable is called a(n) a) main effect. b) simple effect. c) interaction. d) manipulation.

Q: 51 This graph represents a/an a) repeated-measures design b) one-way ANOVA c) 2 X 5 factorial d) significant alpha

Q: 50 When you compare the effect of one variable at one level of another variable you are examining a) a main effect b) a simple effect c) a correlational effect d) both a and c

Q: 49 When comparing differences in an experiment with two or more independent variables we should use a(n) a) one way ANOVA. b) paired sample t-test. c) R squared comparison. d) factorial design.

Q: 48 In this graph we can see that there is a) a significant difference between Location 1 at time 1 and Location 2 at time 1. b) an interaction between location and time. c) a significant post hoc analysis. d) a quadratic significant correlation.

Q: 47 In a factorial design involving the sex of the participant and the sex of the experimenter's confederate a) there were multiple subjects in each cell of the design. b) there were different subjects in each cell of the design. c) all possible combinations of sex of subject and sex of confederate were represented. d) all of the above

Q: 46 A factorial design has at least a) one dependent variable and one independent variable. b) two dependent variables and one independent variable. c) two independent variables and one dependent variable. d) The number of independent variables is not important.

Q: 45 The finding that women eat less in the company of men then when they are in the company of other women is a(n) a) simple effect. b) interaction. c) factorial effect. d) main effect.

Q: 44 Pliner and Chaiken (1990) wanted to investigate whether the amount of food eaten depended on the gender of the participant and the gender of the confederate. It was observed that women eat less than men overall and that women eat less in the company of men than they do when in the company of other women. The finding that women eat less than men across all conditions is a(n) a) simple effect. b) interaction. c) factorial effect. d) main effect.

Q: 43 _______ are the effect of one variable at one level of the other variable. a) simple effects b) main effects c) interactions d) relationships

Q: 42 A pediatrician is studying weight gain in infants. He divides them into 2 groups: breast fed and bottle fed. Further, he divides them into those whose mothers feed them on a timed schedule, and those whose mothers feed them when they cry (on demand). Weight gain is the dependent measure. What type of analysis should you run? a) a regression b) a one-way ANOVA c) a 2 X 2 factorial ANOVA d) a 2 X 2 correlation

Q: 41 In a factorial ANOVA, the interaction is best defined as: a) the effects of one variable are dependent on the level of another variable. b) the effects of one variable without regard to the other variable. c) the effects of one variable at one level of another variable. d) the effects of both independent variables on the dependent variable.

Q: 40 Which of the following has a main effect for Gender and a significant interaction? (Give the best answer.)a) b)c) d)

Q: 39 Suppose you are interested in convincing high school students to avoid taking drugs, and you have three different videos you could show them. You want to know whether there is a difference in effectiveness of the videos, and whether the effectiveness differs for males and females. You set up a design of different students to watch the films as a 2 X 3 ANOVA with a rating of tendency to avoid drugs as the dependent variable. Film A Film B Film C Male Female

Q: 38 If is calculated to yield the magnitude of effect estimates instead of for a particular experiment, the estimates would probably bea) higher and more biased.b) higher and less biased.c) lower and more biased.d) lower and less biased.

Q: 37+ In a study which investigated the effects of amount of coffee consumption and mood (good or bad) on driving speed, the magnitude of effects estimates were as follows: Coffee: ; Mood: ; Coffee x Mood: . Together, how much of the variability in driving speed is accounted for by Coffee, Mood, and their interaction? a) cannot determine b) .49 c) .51 d) .19

Q: 36 To calculate the magnitude of effect estimates for a factorial design, the methods are a) radically different from the methods used with a one-way design. b) simple extensions of the methods used with a one-way design. c) not possible to calculate. d) only useful for estimating magnitude of effects for interactions, not main efforts.

Q: 35+ The following is a printout from SPSS.From this table, which of the following conclusions would be wrong?a) There is a significant effect for Groups.b) There is a significant effect for Education.c) The interaction is significant.d) Both main effects are significant.

Q: 34+ In the factorial design analyses discussed in Chapter 17, the different cells a) often have different subjects in them. b) never have different subjects in them. c) always have different subjects. d) can have either the same subjects or different subjects.

Q: 33 Unequal sample sizes in a factorial analysis of variance are a) no problem. b) often difficult to interpret. c) impossible to interpret. d) easily explained by the use of simple effects.

Q: 32+ Unequal sample sizes in a factorial analysis of variance a) are difficult to deal with when doing calculations by hand. b) are treated exactly as they were in the one-way design. c) cannot be dealt with at all. d) are dealt with just like equal sample sizes when doing hand calculations.

Q: 31 If you have a significant interaction, a) at least one of the main effects will be nonsignificant. b) both of the main effects will be nonsignificant. c) at least one simple effect is likely, though not certain, to be significant. d) the interaction doesn"t suggest anything about simple effects.

Q: 30+ To calculate the F for a simple effect you a) often use the same error term you use for main effects. b) use the mean square for the main effect as the denominator in F. c) first divide the mean square for the simple effect by its degrees of freedom. d) none of the above

Q: 29 A simple effect is calculated by a) looking only at the data for one level of one of the independent variables. b) averaging across the levels of one of the independent variables. c) ignoring one of the independent variables. d) dividing the main effect by the degrees of freedom.

Q: 28 In graph I above, the most apparent simple effect is for the line represented by a) diamonds. b) squares. c) triangles. d) It is unlikely for there to be a simple effect for any level of the independent variable.

Q: 27+ In the three graphs above, which one is most likely to have a main effect for quarters (the variable that increases along the X axis)? a) I b) II c) III d) none.

Q: 26+ Which of the following graphs is most likely to portray an interaction?(I)(II) (III)a) Ib) IIc) IIId) There is no interaction in any of these.

Q: 25 If you have a significant interaction, you should a) think carefully about any main effects you might have. b) ignore any main effects you might have. c) ignore the interaction unless there is a main effect. d) none of the above

Q: 24 In a factorial analysis of variance you cannot have a) both a significant interaction and a significant main effect. b) two significant main effects. c) a significant main effect and a nonsignificant interaction. d) Any combination is possible.

Q: 23+ To calculate the F for the interaction in an analysis of variance we a) divide the MSinteraction by MSerror. b) divide the MSinteraction by MStotal. c) multiply MSinteraction by its df. d) divide MSinteraction into MSrows.

Q: 22 The degrees of freedom for an interaction in a two-way factorial are equal to a) the degrees of freedom for the main effects. b) the sum of the degrees of freedom for the main effects. c) the product of the degrees of freedom for the main effects. d) 6.

Q: 21+ Which of the following is NOT true in a factorial analysis of variance? a) SStotal = SSA + SSB + SSAB b) SStotal = SSA + SSB + SSAB + SSerror c) SScells = SSA + SSB + SSAB d) SStotal = SScells + SSerror

Q: 20 To calculate the sum of squares for a treatment effect in the analysis of variance, we would work with a) the squares of the differences between the treatment means and the grand mean. b) the variance within the treatments. c) the number of samples. d) both a and b

Q: 19 A simple effect is defined as a) part of the interaction. b) the effect of one variable taken by itself. c) the effect of one variable at a single level of the other variable. d) the difference between the row effect and the column effect.

Q: 18 To look at an interaction effect we must a) consider one variable at a time. b) plot the data within each cell. c) plot the data in such a way that we see how each independent variable changes at each level of the other independent variable. d) calculate the row means.

Q: 17 The main effect of a variable is a) the effect of that variable controlling for another variable. b) the effect of that variable averaged over the levels of other independent variable(s). c) part of the interaction effect. d) none of the above

Q: 16 In the text the Eysenck study of recall as a function of Age and Instructions allowed us to see that a) older subjects don"t recall as well as earlier subjects, on average. b) older and younger subjects differ more on tasks which involve greater depth of processing. c) greater processing tends to lead to better recall. d) all of the above

Q: 15 The notation stands for a) the mean of any row. b) the mean of any column. c) the mean of any cell. d) the grand mean.

Q: 14 In a factorial design a cell is a) the combination of a row and a column. b) the smallest number of subjects who were treated alike. c) another name for a simple effect. d) both a and b

Q: 13 Which of the following is not an advantage of factorial designs over one-way designs? a) They allow for greater generalizability. b) They allow us to test an interaction. c) They make it easier to deal with unequal sample sizes. d) They give us greater economy.

Q: Source df SS MS F pGender 1 240.25 240.250 29.94 .000Group 4 1514.94 378.730 47.19 .000GenderxGroup 4 190.30 47.575 5.93 .002Residual 90 722.30 8.026 Total 99 2667.79 12+ How many cells are there in this design?a) 1b) 4c) 8d) 10

Q: Source df SS MS F pGender 1 240.25 240.250 29.94 .000Group 4 1514.94 378.730 47.19 .000GenderxGroup 4 190.30 47.575 5.93 .002Residual 90 722.30 8.026 Total 99 2667.79 11+ What does the significant F for Group most likely mean?a) All the groups are different from each other.b) None of the groups are different from each other.c) The study has problems with control.d) There is at least one significant difference among the groups.

Q: Source df SS MS F pGender 1 240.25 240.250 29.94 .000Group 4 1514.94 378.730 47.19 .000GenderxGroup 4 190.30 47.575 5.93 .002Residual 90 722.30 8.026 Total 99 2667.79 10+ Why does Group have 4 degrees of freedom?a) because there are 4 groupsb) because there are 5 groups (5 - 1 = 4)c) because gender has 1 df (1 x 4 = 4)d) because the design has four cells

Q: Source df SS MS F pGender 1 240.25 240.250 29.94 .000Group 4 1514.94 378.730 47.19 .000GenderxGroup 4 190.30 47.575 5.93 .002Residual 90 722.30 8.026 Total 99 2667.79 9+ The summary table suggests which of the following conclusions?a) a main effect of genderb) a main effect of groupc) an interaction of gender ï‚´ groupd) all of the above

Q: 8 What would you suggest if the researcher found that alcohol consumption increased rape myth acceptance, but only when the participants had watched the owl video?a) There is an interaction between alcohol consumption and video type.b) There is a main effect of alcohol consumption.c) There is a simple effect of alcohol in the educational video condition.d) There is a main effect of the video condition.

Q: 7+ What type of statistical analysis would be most appropriate for this experiment? a) a t-test b) a regression c) a one-way analysis of variance d) a factorial analysis of variance

Q: 6 How many cells does this experiment have? a) 2 b) 5 c) 6 d) 12

Q: 5 The results indicated that the participants who watched the educational video scored significantly lower on the rape myth scale compared to the group that watched the owl video. What does this suggest? a) There is a main effect of alcohol consumption. b) There is a main effect of video type. c) There is an interaction between alcohol consumption and video type. d) For some unknown reason, owls seem to promote rape myth acceptance.

Q: 4 If the analysis of variance is significant, we are pretty sure that a) we have an important finding. b) at least one mean is different from one or more other means. c) the means don"t differ from each other. d) we screwed up somewhere.

Q: 3 The difference between a one-way analysis of variance and a factorial analysis of variance is a) the presence of an interaction. b) the presence of more than one main effect. c) one-way analyses of variance have an error term, whereas factorial analyses do not. d) both a and b

Q: 2 A 2 ï‚´ 4 factorial has a) 8 subjects. b) 2 levels of one variable and 4 levels of the other. c) 8 factors. d) one variable with 4 levels and 2 subjects.