Statistics For The Behavioral And Social Sciences A Brief Course 6th Edition Arthur Aron Elliot J Blows Elaine N Aron - Solutions

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Chi-square uses squared discrepancies so that the result is not affected by the directions of the differences. It is divided by the expected number to adjust for the relatively different numbers expected in the combinations.
what is the
how well it actually measures what it is intended to measure. A measure has content validity if it gets at all the different aspects of what it is intended to measure.
5. The three types of measures that are used most often in behavioral and social sciences research are self-report, behavioral, and physiological measures. Researchers evaluate a measure in terms of its reliability and validity. A measure’s reliability is its accuracy or consistency. The most
4. Random selection is the best method for ensuring that a sample is representative of its population.
3. In practice, it can be quite difficult to test experimental and control groups under identical circumstances. The most common problems that can affect the equivalence of circumstances are placebo effects, Hawthorne effects, and experimenter effects.
(1) random assignment to groups; (2) matched-group designs; (3)repeated-measures designs; (4) correlational research designs; and (5)single-subject research. There are advantages and disadvantages to each of these approaches.
2. There are several approaches available to researchers in order to maintain the equivalence of experimental and control groups, including
identical situations; (3) the sample studied perfectly represents the intended population; and (4) the dependent variable is measured in a completely accurate and appropriate manner for what it is supposed to be measuring.
identical; (2) the experimental and control groups are exposed to
3. Determine the cutoff sample score on the comparison distribution at which the null hypothesis should be rejected..05 level, df=4: χ2 needed=9.488..• A true experiment systematically varies the level of one variable (for example, an independent variable, X) and looks at the effect on another
2. Determine the characteristics of the comparison distribution.Chi-square distribution with four degrees of freedom. df=(NColumns−1)(NRows−1)=(3−1)(3−1)=4.
3. (a) and (b) Graphs of the same kind as in 8(i) (a) and (b) above; (c)main effects for brand and type and an interaction; (d) flavor is rated on the average more positively for regular than decaf and brands Z and X are rated more favorably than Y. However, there is an interaction in which there
Chicago lowest. Restaurant quality is different in different price ranges, with expensive the best and inexpensive the least. The two factors do not simply combine, however, as price makes more difference in New York than in other cities.
2. (a) and (b) Graphs of the same kind as in 8(i) (a) and (b) above; (c)main effect for city and cost, plus an interaction; (d) restaurant quality is different in different cities, with New York highest and
1. (a) and (b) Graphs of the same kind as in 8(i) (a) and (b) above; (c)main effect for relationship and an interaction; (d) conversations are longer with friends; but the difference is much greater for personal than for nonpersonal topics.
3. (a) and (b) Graphs of the same kind as in (i) (a) and (b) above; (c)both main effects significant, no interaction; (d) females miss fewer days per month than males; those who exercise miss fewer days per month than controls. Each combination misses the number of days you would expect knowing
if one considers the combinations: Grades are highest for community college arts majors and for liberal arts college science majors.
2. (a) and (b) Graphs of the same kind as in (i) (a) and (b) above; (c)no main effects, interaction effect; (d) neither type of college nor type of major, by itself, predicts grades, but there is a clear pattern
2. Effect size, R2=(SBetween2)(dfBetween)/[(SBetween2)(dfBetween)+(SWithin2)(dfWithin)]=.62.
5. Decide whether to reject the null hypothesis. F from Step(7.38) is more extreme than cutoff F from Step (4.26);reject the null hypothesis.
3. Determine the cutoff sample score on the comparison distribution at which the null hypothesis should be rejected.5% level, F (2, 9) needed = 4.26.
2. Determine the characteristics of the comparison distribution. F distribution with 2 and 9 degrees of freedom.
1. Restate the question as a research hypothesis and a null hypothesis about the populations. There are three populations of interest:Population 1: Patients with affective disorders.Population 2: Patients with personality disorders.Population 3: Patients with drug-related conditions.The null
27. In a recent issue of a journal in an area of behavioral and social sciences that especially interests you, find an article that uses one of the statistical procedures described in this chapter. Write a brief summary of the study, referring specifically to the statistics. With your answer,
26. This question refers to another part of the study by DeGarmo and Forgatch (1997), described in problem 23. These researchers studied a group of divorced mothers, focusing on the support they received from their closest confidant. That confidant was sometimes a close friend, sometimes a family
Explain what is being done, using this result as an example, to someone who is familiar with ordinary analysis of variance, but who is not familiar with the analysis of covariance.
when… mood scores were partialed out, F(1, 10)=12.93, p
a series of analyses of covariance … tested whether the Mozart effect would remain in evidence when individual differences in enjoyment, arousal, and mood were statistically controlled. For each analysis … the covariate represented the scores on one of[these] measures. Although the Mozart
25. Thompson, Schellenberg, and Husain (2001) conducted a study of the“Mozart effect”—that listening to music composed by Mozart improves performance on tasks involving spatial abilities. In their initial analysis, the researchers found that participants did better on a paper-folding task
3. A study of voting preferences of people from three different regions of Canada.
2. A study comparing women in the United States versus women in Denmark on their attitudes toward preschool education.
1. A study of speed of performance on a complex task, in which one group does the task at night and the other in the morning.
24. In each of the following (fictional) studies, indicate which variable is the independent variable and which is the dependent variable:
a) Explain the pattern of results, ignoring the curved arrows, which represent nondirectional associations (that is, correlations; the “D”s stand for “disturbance”, which are error terms that we mentioned briefly earlier in the chapter). (b) Using this diagram as an example, explain the
2. A study of the association between two variables.
1. A study in which the researcher has a complex theory of the pattern of cause and effect among several variables.
13. For each of the following (fictional) studies, what would be the most appropriate statistical technique?
Canada) and the type of conflict interaction (interpersonal versus intergroup). The five dependent variables were five measures of conflict resolution preferences.v
Participants were 90 Nigerians (Nigeria was considered an example of a relatively collectivist society) and 95 Canadians (Canada was considered an example of a relatively individualistic society). All participants answered questions about how much they preferred each of five methods of resolving
12. Gire (1997) studied the preferred methods of resolving conflicts, comparing people in individualistic versus collectivistic cultures.
11. Roeser, Vander Wolf, and Strobel (2001) conducted a cross-cultural study of self-esteem comparing adolescents from the United States and the Netherlands. In their article they had a section labeled “Covariates”in which they note, “A measure of social desirability was included in each
3. A study of number of touches between two infants playing in the same room, comparing when their mothers are present versus when their mothers are not present.
2. A study looking at heart rate change while watching one of three kinds of movies (horror movie, love story, or comedy).
1. A study examining the number of households that recycle in a neighborhood receiving a recycling awareness campaign compared to the number of households that recycle in a neighborhood that does not receive the campaign.
10. In each of the following (fictional) studies, which variable is the independent variable and which is the dependent variable?
6. Briefly describe the general principle of Bayesian statistical methods.
5. What method would you use if you had more than one independent variable, only one dependent variable, and one or more covariates?
4. (a) How does a multivariate analysis of variance differ from an ordinary analysis of variance? (b) After finding a significant effect in a MANOVA, what is the usual next step? (c) How does a multivariate analysis of covariance differ from an ordinary analysis of covariance?
3. How are multivariate statistics unlike all of the procedures covered previously in this course?
2. (a) What is an analysis of covariance? (b) How is it like partial correlation? (c) What is a covariate?
1. In a t test or analysis of variance, (a) what is the independent variable and (b) what is the dependent variable? (c) How do independent and dependent variables match up with criterion and predictor variables?
7. What is a major limitation of structural equation modeling?
6. How is the significance test in structural equation modeling different from an ordinary significance test?
5. (a) What is a latent variable? (b) What is its relation to measured variables? (c) What is the usual direction of causality between a latent variable and its associated measured variables? (d) Why?
4. (a) What is a fit index? (b) What is considered a good fit on most fit indexes? (c) What is considered a very good fit on the RMSEA?
3. (a) What is mediational analysis? (b) List the four steps for establishing mediation.
2. (a) What is a path diagram? (b) What is a path? (c) What is a path coefficient? (d) In an ordinary path analysis, how do you evaluate whether there is a good overall fit of the model to the correlations in the sample?
1. What is the purpose of causal modeling?
5. In the example of factor analysis shown in Table 12–3, what are the factor loadings for item 4 (I enjoy checking my Facebook account) on each factor?
4. (a) When do you use a factor analysis? (b) What information does it give you? (c) What is a factor? (d) What is a factor loading? (e) What is the most subjective part of factor analysis?
3. In the example of reliability shown in Table 12–2, what is the internal consistency reliability and test–retest reliability for the Random subscale.
2. (a) What is the reliability of a measure? (b) List and define three kinds of reliability.
How can partial correlation help sort out direction of causality in a correlational study?
1. (a) What is partial correlation? (b) What does it mean if a partial correlation is less than the original correlation? (c) What does it mean if a partial correlation is about the same as the original correlation? (d)
What is the upper-level variable? (c) and (d) Describe the two steps you would use to carry out the analysis using the old-fashioned standard method.
6. An organizational researcher conducts a study of sales people in 38 department stores (with about 150 salespeople per store and with the stores varying from “big box” discount stores to exclusive high-end stores). The researcher plans to conduct a multilevel modeling analysis to find out
5. Under what conditions would you use multilevel modeling?
4. How are hierarchical and stepwise regression (a) similar and (b)different?
3. (a) How does the common method of stepwise regression work? (b)What is the usual reason it is done? (c) What is a major limitation of this procedure?
2. (a) How does hierarchical regression work? (b) What is the usual reason it is done?
1. Write the formula for multiple regression with Z scores for three predictors and define each of the symbols.
5. Decide whether to reject the null hypothesis. The sample’s chisquare of 16.07 is larger than the cutoff of 9.211. Thus, you can reject the null hypothesis. The research hypothesis that the two variables are not independent in the population is supported. That is(based on this fictional study),
6. Add up the results of Step for all the cells.3+0+3.43+4.50+0+5.14=16.07.
5. Divide each squared difference by the expected frequency for its cell. For example, for the Night Person/Own Car cell, this comes out to 5.14 (that is, 144/28=5.14).
4. Square each of these differences. For example, for the Night Person/Own Car cell, this comes out to 144 (that is, 122=144).
3. In each cell, take observed minus expected frequencies. For example, for the Night Person/Own Car cell, this comes out to 12 (that is 40−28=12).
2. For each cell, multiply its row’s percentage by its column’s total. The column total for those with their own car is 70; 40% of 70 comes out to 28 (that is, .40×70=28).
2. Determine the expected frequencies in each cell. For example, for the bottom right cell (Night Person/Own Car cell),
1. Determine the actual, observed frequencies in each cell. These are shown in the contingency table for the problem.
5. Decide whether to reject the null hypothesis. The sample’s chisquare of 18.75 is more extreme than the cutoff of 3.841. Reject the null hypothesis; people like those in the sample are different from the expected 60% to 40% breakdown.4
6. Add up the results of Step for all the categories.7.5+11.25=18.75.
5. Divide each squared difference by the expected frequency for its category. For the first category, this comes out to 7.5 (that is, 225/30=7.5). For the second category, this comes out to 11.25 (that is, 225/20=11.25).
4. Square each of these differences. Both come out to 225 (that is, −152=225 and 152=225).
3. In each category, take observed minus expected frequencies.These come out to −15 (that is, 15−30=−15) and 15 (that is, 35−20=15).
2. Determine the expected frequencies in each category. With 50 people total and expecting a 60% to 40% breakdown, the expected frequencies are 30 and 20.
1. Determine the actual, observed frequencies in each category.As given in the problem, these are 15 and 35.
4. Determine your sample’s score on the comparison distribution.
3. Determine the cutoff sample score on the comparison distribution at which the null hypothesis should be rejected. At the .05 level with df=1, cutoff is 3.841.
2. Determine the characteristics of the comparison distribution. The comparison distribution is a chi-square distribution with 1 degree of freedom (that is, df=NCategories−1=2−1=1).
1. Restate the question as a research hypothesis and a null hypothesis about the populations. There are two populations:Population 1: People like those in the sample.Population 2: People in general who have a distribution of 60% in the first category and 40% in the second category.The research
3. 3. Formula for the chi-square statistic: χ2=Σ(O−E)2E.χ2 is the chi-square statistic; Σ tells you to sum over all the different categories; O is the observed frequency for a category; E is the expected frequency for a category.
“The self-reports on the Attentiveness to Alternative Index and the time spent actually inspecting the attractive opposite-sex slides … were positively skewed, so logarithmic transformations of the data were performed” (p. 760). Explain what is being described here (and why it is being done)
12. Miller (1997) conducted a study of commitment to a romantic relationship and how much attention a person pays to attractive alternatives. In this study, participants were shown a set of slides of attractive individuals. At the start of the Results section, Miller notes,
(c) Carry out an analysis of variance using the transformed scores. (d)Explain what you have done and why to someone who is familiar with analysis of variance but not with data transformation.
how honest they appear. The ratings for the sad-film group were 201, 523, and 614; the ratings for the angry-film group were 136, 340, and 301; and the ratings for the exuberant-film group were 838, 911, and 1,007. (a) Carry out an analysis of variance using the actual scores (use p
11. A researcher randomly assigns participants to watch one of three kinds of films: one that tends to make people sad, one that tends to make people angry, and one that tends to make people exuberant. The participants are then asked to rate a series of photos of individuals on
10. A researcher compares the typical family size in 10 cultures, 5 from Language Group A and 5 from Language Group B. The figures for the Group A cultures are 1.2, 2.5, 4.3, 3.8, and 7.2. The figures for the Group B cultures are 2.1, 9.2, 5.7, 6.7, and 4.8. Based on these 10 cultures, does typical
9. For each of the following distributions, make a square-root transformation:1. 16, 4, 9, 25, 36 2. 35, 14.3, 13, 12.9, 18
3. Explain the results to parts (a) and (b) to a person who has never had a course in statistics.

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Statistics For The Behavioral And Social Sciences A Brief Course 6th Edition Arthur Aron Elliot J Blows Elaine N Aron - Solutions

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