Q&A Hero

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.

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