Question 14.1

Question 14.2

Question 14.3

Question 14.4

Question 14.5

Question 14.6

Question 14.7

Question 14.8

Question 14.9

Question 14.10

Question 14.11

Question 14.12

Question 14.13

Question 14.14

Question 14.15

Question 14.16

Question 14.17

Question 14.18

Question 14.19

Question 14.20

Question 14.21

Question 14.22

For each of the following scenarios, what are two names for the ANOVA that would be conducted to analyze the data?

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Question 14.23

Identify the factors and their levels in the following research designs.

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Question 14.24

State how many cells there should be for each of these studies. Then, create an empty grid to represent those cells.

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3. 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

Question 14.25

Use these “enjoyment” data to perform the following:

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9. cm9u2wFBAtN9BQLJREX33Fq1l7YrRPPdrZw4n9bagUv+ctry/2EFRg==

Question 14.26

Use these data—incidents of reports of underage drinking— to perform the following:

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Question 14.27

Question 14.28

Question 14.29

Question 14.30

Football, eye glare, and ANOVA: In Exercise 13.25 (page 346), we described a Yale University study. Let’s consider a redesign in which researchers randomly assigned 46 participants to place one of three substances below their eyes: black grease, black antiglare stickers, or petroleum jelly. They assessed eye glare using a contrast chart that gives a value for each participant, a scale measure. Black grease led to a reduction in glare compared with the two other conditions, antiglare stickers or petroleum jelly (DeBroff & Pahk, 2003). Imagine that every participant was tested twice, once in broad daylight and again under the artificial lights used at night.

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2. Eqv/rhT5NoqJbmHMu5dldu9TjtQKI+n8xDW9Kh1CQm63akKbRohA7O5KN9YUbK9V

385

Question 14.31

Health-related myths and the type of ANOVA: Consider the study we used as an example for a two-way between-groups ANOVA. Older and younger people were randomly assigned to hear either one repetition or three repetitions of a health-related myth, accompanied by the accurate information that “busted” the myth.

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Question 14.32

Memory and choosing the type of ANOVA: In a fictional study, a cognitive psychologist studied memory for names after a group activity. The researcher randomly assigned 120 participants to one of three conditions: (1) group members introduced themselves once, (2) group members were introduced by the experimenter and by themselves, and (3) group members were introduced by the experimenter and themselves, and they wore name tags throughout the group activity.

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Question 14.33

Age, online dating, and choosing the type of ANOVA: A researcher wondered about the degree to which age was a factor for those posting personal ads on Match.com. He randomly selected 200 ads and examined data about the posters (the people who posted the ads). Specifically, for each ad, he calculated the difference between the poster’s age and the oldest acceptable age in a romantic prospect. So, if someone were 23 years old and would date someone as old as 30, his or her score would be 7; if someone were 25 and would date someone as old as 23, his or her score would be −2. The researcher then categorized the scores into male versus female and seeking a same-sex date versus seeking an opposite-sex date.

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2. TupEhpJe9+n112TpLjrMVzCs5i7zYEgZh2Q3kuxeEw6wxopC9PUyl5tOzrs3scbN
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Question 14.34

Racism, juries, and interactions: In a study of racism, Nail, Harton, and Decker (2003) had participants read a scenario in which a police officer assaulted a motorist. Half the participants read about an African American officer who assaulted a European American motorist, and half read about a European American officer who assaulted an African American motorist. Participants were categorized based on political orientation: liberal, moderate, or conservative. Participants were told that the officer was acquitted of assault charges in state court but was found guilty of violating the motorist’s rights in federal court. Double jeopardy occurs when an individual is tried twice for the same crime. Participants were asked to rate, on a scale of 1–7, the degree to which the officer had been placed in double jeopardy by the second trial.

The researchers reported the interaction as F(2, 58) = 10.93, p < 0.0001. The means for the liberal participants were 3.18 for those who read about the African American officer and 1.91 for those who read about the European American officer. The means for the moderate participants were 3.50 for those who read about the African American officer and 3.33 for those who read about the European American officer. The means for the conservative participants were 1.25 for those who read about the African American officer and 4.62 for those who read about the European American officer.

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Question 14.35

Self-interest, ANOVA, and interactions: Ratner and Miller (2001) wondered whether people are uncomfortable when they act in a way that’s not obviously in their own self-interest. They randomly assigned 33 women and 32 men to read a fictional passage saying that federal funding would soon be cut for research into a gastrointestinal illness that mostly affected either (1) women or (2) men. They were then asked to rate, on a 1–7 scale, how comfortable they would be “attending a meeting of concerned citizens who share your position” on this cause (p. 11). A higher rating indicates a greater degree of comfort. The journal article reported the statistics for the interaction as F(1, 58) = 9.83, p < 0.01. Women who read about women had a mean of 4.88, whereas those who read about men had a mean of 3.56. Men who read about women had a mean of 3.29, whereas those who read about men had a mean of 4.67.

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Question 14.36

Gender, negotiating a salary, and an interaction: Eleanor Barkhorn (2012) reported in the Atlantic about differences in women’s and men’s negotiating styles. She first explained that researchers did not find a significant difference in how likely women and men are to negotiate salaries. But this did not tell the whole story. Barkhorn wrote: “Women are more likely to negotiate when an employer explicitly says that wages are negotiable. Men, on the other hand, are more likely to negotiate when the employer does not directly state that they can negotiate.”

For each of the following, state whether the finding is a result of examining a main effect or examining an interaction. Explain your answer.

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Question 14.37

The cross-race effect, main effects, and interactions: Hugenberg, Miller, and Claypool (2007) conducted a study to better understand the cross-race effect, in which people have a difficult time recognizing members of different racial groups—colloquially known as the “they all look the same to me” effect. In a variation on this study, white participants viewed either 20 black faces or 20 white faces for 3 seconds each. Half the participants were told to pay particular attention to distinguishing features of the faces. Later, participants were shown 40 black faces or 40 white faces (the same race that they were shown in the prior stage of the experiment), 20 of which were new. Each participant received a score that measured his or her recognition accuracy.

The researchers reported two effects, one for the race of the people in the pictures, F(1, 136) = 23.06, p < 0.001, and one for the interaction of the race of the people in the pictures and the instructions, F(1, 136) = 5.27, p < 0.05. When given no instructions, the mean recognition scores were 1.46 for white faces and 1.04 for black faces. When given instructions to pay attention to distinguishing features, the mean recognition scores were 1.38 for white faces and 1.23 for black faces.

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Question 14.38

Grade point average, fraternities, sororities, and two-way between-groups ANOVA: A sample of students from our statistics classes reported their GPAs, indicated their genders, and stated whether they were in the university’s Greek system (i.e., in a fraternity or sorority). Following are the GPAs for the different groups of students:

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Question 14.39

Age, online dating, and two-way between-groups ANOVA: The data below were from the same 25-year-old participants described in How It Works 14.1, but now the scores represent the oldest age that would be acceptable in a dating partner.

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Question 14.40

Helping, payment, and two-way between-groups ANOVA: Heyman and Ariely (2004) were interested in whether effort and willingness to help were affected by the form and amount of payment offered in return for effort. They predicted that when money was used as payment, in what is called a money market, effort would increase as a function of payment level. On the other hand, if effort were performed out of altruism, in what is called a social market, the level of effort would be consistently high and unaffected by level of payment. In one of their studies, college students were asked to estimate another student’s willingness to help load a sofa into a van in return for a cash payment or candy of equivalent value. Willingness to help was assessed using an 11-point scale ranging from “Not at all likely to help” to “Will help for sure.” Data are presented here to re-create some of their findings.

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Question 14.41

Helping, payment, and interactions: Expanding on the work of Heyman and Ariely (2004) as described in Exercise 14.40, let’s assume a higher level of payment was included and the following data were collected. (Notice that all data are the same as earlier, with the addition of new data under a high payment amount.)

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388

Question 14.42

Exercise, well-being, and type of ANOVA: Cox, Thomas, Hinton, and Donahue (2006) studied the effects of exercise on well-being. There were three independent variables: age (18–20 years old, 35–45 years old), intensity of exercise (low, moderate, high), and time point (15, 20, 25, and 30 minutes). The dependent variable was positive well-being. Every participant was assessed at all intensity levels and all time points. (Generally, moderate-intensity exercise and high-intensity exercise led to higher levels of positive well-being than did low-intensity exercise.)

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Question 14.43

Body weight, salary, and the need for covariates: A nutritional software program called DietPower offers encouragement to its users when they sign in each day. In one instance, the program states that people at their ideal body weight tend to have higher salaries than do people who are overweight and then explicitly states that losing weight might lead to an increase in pay!

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Question 14.44

Math performance and type of ANOVA: Imagine that a college professor is interested in the effects of a new instructional method on the math performance of first-year college students. All students take a math pretest and then are randomly assigned to a class in which the new instructional method is used or a class in which the old method is used. At the end of the semester, the professor gives all students the same final exam and has all students complete a national standardized test that assesses math ability.

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Question 14.45

College students, anxiety, depression, and a MANOVA: Jason Nelson and Noel Gregg (2012) conducted a study of college students with disabilities. They reported that: “A 3 × 3 × 2 MANOVA was conducted to determine the effect of level of educational attainment (transitioning adolescents and college underclassmen—that is, freshmen and sophomores—and college upperclassmen—that is, juniors and seniors), disability status (dyslexia, ADHD, and ADHD/dyslexia), and gender on BDI-II and BAI scores” (p. 249). (The BDI is the Beck Depression Inventory, which assesses symptoms of depression; the BAI is the Beck Anxiety Inventory, which assesses symptoms of anxiety.)

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Question 14.46

Skepticism, self-interest, and two-way ANOVA: A study on motivated skepticism examined whether participants were more likely to be skeptical when it served their self-interest (Ditto & Lopez, 1992). Ninety-three participants completed a fictitious medical test that told them they had high levels of a certain enzyme, TAA. Participants were randomly assigned to be told either that high levels of TAA had potentially unhealthy consequences or potentially healthy consequences. They were also randomly assigned to complete a dependent measure before or after the TAA test. The dependent measure assessed their perception of the accuracy of the TAA test on a scale of 1 (very inaccurate) to 9 (very accurate). Ditto and Lopez found the following means for those who completed the dependent measure before taking the TAA test: unhealthy result, 6.6; healthy result, 6.9. They found the following means for those who completed the dependent measure after taking the TAA test: unhealthy result, 5.6; healthy result, 7.3. From their ANOVA, they reported statistics for two findings. For the main effect of test outcome, they reported the following statistic: F(1,73) = 7.74, p < 0.01. For the interaction of test outcome and timing of the dependent measure, they reported the following statistic: F(1, 73) = 4.01, p < 0.05.

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Question 14.47

Feedback and ANOVA: Stacey Finkelstein and Ayelet Fishbach (2012) examined the impact of feedback in the learning process. The following is an excerpt from their abstract: “This article explores what feedback people seek and respond to. We predict and find a shift from positive to negative feedback as people gain expertise. We document this shift in a variety of domains, including feedback on language acquisition, pursuit of environmental causes, and use of consumer products. Across these domains, novices sought and responded to positive feedback, and experts sought and responded to negative feedback” (p. 22).

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