Question 1

Complete this analogy: Elaboration is to interaction effects as…
A) regression is to crosstabulation
B) crosstabulation is to regression
C) regression is to standard deviation
D) frequency distribution is to regression

Accepted Answer

Elaboration is a process used in qualitative research to explore the relationships between variables, often revealing interaction effects. Crosstabulation is a method used to examine the relationship between two categorical variables, which can help in understanding interaction effects in a more descriptive manner. Regression, on the other hand, is a statistical method used to model the relationship between a dependent variable and one or more independent variables, making choice B the best analogy as it aligns the qualitative exploration of relationships (elaboration) with a more quantitative, yet still fundamentally relational analysis (regression).

Question 2

Which of the following is not a reason to choose interaction over elaboration?
A) The crosstabs tend to be too large
B) It is difficult to control for more than one variable in a crosstab
C) Some of the cells in the crosstabs may have very small frequencies
D) R-squared is better than chi-square

Accepted Answer

R-squared is a measure of the strength of the relationship between two variables in a regression analysis, whereas chi-square is a measure of the independence between two variables in a crosstab. The decision to choose interaction over elaboration should not be based on the superiority of one statistical measure over another, but on the research question and the nature of the variables being analyzed. Choices A, B, and C are all valid reasons to choose interaction over elaboration, as they highlight some of the limitations of crosstabulation analysis.

Question 3

Let's say we're creating an interaction effect between sex and years of education. If sex is coded Male=0, Female=1, what is the value of the interaction effect for a woman with 16 years of education?
A) 0
B) 16
C) 15
D) 4

Accepted Answer

The interaction effect is calculated by multiplying the values of the two interacting variables. Here, for a woman (sex coded as 1) with 16 years of education, the interaction effect is 1 * 16 = 16.

Question 4

Let's say we're creating an interaction effect between sex and years of education. If sex is coded Male=0, Female=1, what is the value of the interaction effect for a man with 16 years of education?
A) 0
B) 16
C) 15
D) 4

Accepted Answer

The interaction effect is calculated by multiplying the values of the two interacting variables. For a man (sex coded as 0), regardless of the years of education, the interaction effect will always be 0 because 0 (for male) multiplied by any value (years of education) equals 0.

Question 5

In a regression equation that uses sex (Male=0, Female=1), years of education, and the interaction effect between sex and education, the resulting graphs are two parallel lines. Which of the following must be true?
A) The slope for sex is not statistically significant.
B) The slope for education is not statistically significant.
C) The slope for the interaction effect is not statistically significant.
D) None of the three slopes is statistically significant.

Accepted Answer

Since the resulting graphs are parallel lines, it indicates that there is no interaction between sex and years of education. Therefore, the slope for the interaction effect is not statistically significant. However, the slopes for sex and education may still be statistically significant, and it is not necessary for all three slopes to be insignificant.

Question 6

In a regression equation that uses sex (Male=0, Female=1), the slope for sex has the same exact value as the interaction slope, but a different sign. What best describes the line for women?
A) Its slope will be twice that of the men's slope.
B) Its slope will be half that of the men's slope.
C) It will be completely vertical.
D) It will be completely horizontal.

Accepted Answer

The answer of In a regression equation that uses sex...

Question 7

Here is a regression model using GSS2006 data. All slopes are statistically significant.
Dependent Variable: Respondent's Age at First Marriage
$\begin{array}{lc}
\text { Independent Variable } & \text { Slope } \
\text { Respondent's Years of Education } & .35 \
\text { Respondent's Race (White }=0 \text {, Black }=1) & 14.62 \
\text { Interaction: Education x Race } & -.92 \
\text { Constant } & 18.29
\end{array}$ Which of the following is the best description of the resulting graphed lines?
A) Both lines have positive slopes, but the black line has a steeper slope.
B) Both lines have positive slopes, but the white line has a steeper slope.
C) The white line has a positive slope, the black line has a negative slope.
D) The white line has a negative slope, the black line has a positive slope.

Accepted Answer

The answer of Here is a regression model using GSS2006...

Question 8

Here is a regression model using GSS2008 data, respondents aged 18-35. All slopes are statistically significant:
Dependent Variable: # of Times Respondent Goes to Bar Per Month
$\begin{array}{lr}
\text { Independent Variable } & \text { Slope } \
\text { Sexual Orientation (Hetero=0, Gay or } \mathrm{Bi}=1) & 5.49 \
\text { Sex (Male=0, Female=1) } & -1.34 \
\text { Interaction: Sexual Orientation x Sex } & -5.39 \
\text { Constant: } & 3.18
\end{array}$
$\begin{array}{ll}
\text { R-Squared: } & .05 \
\mathrm{n}: & 353
\end{array}$ Who goes to bars most frequently?
A) Heterosexual men
B) Heterosexual women
C) A gay/bisexual man
D) A lesbian/bisexual woman

Accepted Answer

A gay or bisexual man goes to bars most frequently. This is determined by adding the constant (3.18) to the slope for sexual orientation (5.49), which indicates that, all else being equal, gay or bisexual men go to bars more often than their heterosexual counterparts. The interaction term and the slope for sex are not added to this calculation because they apply to women or the interaction between sexual orientation and sex, not to gay or bisexual men directly.

Question 9

What is the most common form of interaction effect presented in Chapter 12?
A) an interaction effect between two ratio-level variables
B) an interaction effect between two dichotomies
C) an interaction effect between a ratio-level variable and a dichotomy
D) an interaction effect between a nominal-level variable and a dichotomy

Accepted Answer

Most of the examples used a ratio-level variable and a dichotomy.

Question 10

All of the interaction examples in Chapter 12 involve interacting how many parent variables?
A) 2
B) 3
C) 4
D) 5

Accepted Answer

All of the interaction examples involve interacting two parent variables, such as age and gender, or education level and income.

Question 11

In a regression equation that uses sex (Male=0, Female=1), years of education, and the interaction effect between sex and education, all of the resulting slopes are statistically significant. We find that the two parent slopes have positive values and the slope for the interaction effect has a positive value. Which of the following best describes the resulting graphs?
A) The male line starts above the female line and continues to pull away from the female line.
B) The male line starts above the female line, but the female line starts to catch up with the male line.
C) The female line starts above the male line and continues to pull away from the male line.
D) The female line starts above the male line, but the male line starts to catch up with the female line.

Accepted Answer

The positive slopes for both parent variables (sex and years of education) indicate that as the value of these variables increases, the outcome variable also increases. The positive interaction effect suggests that the increase is even greater for females (coded as 1) as they gain more education, leading to the female line not only starting above the male line but also pulling away further as years of education increase.

Question 12

According to the textbook examples, who is likely to have better health?
A) a poor woman
B) a rich woman
C) a poor man
D) a rich man

Accepted Answer

Research consistently shows that higher socioeconomic status (SES), which includes income, education, and occupation, is associated with better health outcomes. Thus, a rich woman is likely to have better health than a poor woman or a poor man, and may even have better health outcomes than a rich man due to gender differences in health behaviors and medical care utilization.

Question 13

In a regression equation that uses sex (Male=0, Female=1), years of education, and the interaction effect between sex and education, all of the resulting slopes are statistically significant. We find that the two parent slopes have positive values and the slope for the interaction effect has a negative value half the size of the slope for education. Which of the following best describes the resulting graphs?
A) The male line starts above the female line and continues to pull away from the female line.
B) The male line starts above the female line, but the female line starts to catch up with the male line.
C) The female line starts above the male line and continues to pull away from the male line.
D) The female line starts above the male line, but the male line starts to catch up with the female line.

Accepted Answer

The positive slope for education means both lines increase with education. The negative interaction effect means the female line's slope is less steep, so the male line catches up.

Question 14

Which statement best describes the relationship between BMI and income?
A) Both men and women experience decreases in income as BMI increases, but women more so.
B) Both men and women experience decreases in income as BMI increases, but men more so.
C) As men's BMI increases, their income goes up, but as women's BMI increases, their income goes down.
D) As women's BMI increases, their income goes up, but as men's BMI increases, their income goes down.

Accepted Answer

Research indicates that as men's BMI increases, their income tends to increase, while the opposite trend is observed for women, where an increase in BMI is associated with a decrease in income. This reflects societal biases and differing standards of physical appearance in the workplace.

Question 15

In Kisida, Greene, and Bowen's research on art museums, what was the name of the art museum they studied?
A) Crystal Bridges
B) Heather Meadows
C) Amber Towers
D) Whitney Modern

Accepted Answer

The research conducted by Kisida, Greene, and Bowen focused on the effects of visiting Crystal Bridges art museum on individuals' empathy and tolerance.

Question 16

What combination of methods did Kisida, Greene, and Bowen use in their research on art museums?
A) survey research and content analysis
B) survey research and experimentation
C) content analysis and experimentation
D) content analysis and analysis of census data

Accepted Answer

The researchers used a combination of survey research and experimentation. They conducted a survey of museum-goers and also conducted an experiment where they randomly assigned participants to either view a particular artwork with or without additional contextual information.

Question 17

What behavioral measure did Kisida, Greene, and Bowen use?
A) whether or not the student used a coupon to see a special art exhibit
B) whether or not the student asked a question during the museum tour
C) whether or not the student told their parents about their museum tour
D) whether or not the student passed an art quiz after their museum tour

Accepted Answer

Kisida, Greene, and Bowen used whether or not the student used a coupon to see a special art exhibit as a behavioral measure in their study.

Question 18

According to Kisida, Greene, and Bowen's research on art museums, which type of student was most likely to benefit from attending the museum program?
A) a student who previously did no cultural activities and who went to a school with a low percentage of free/reduced lunches.
B) a student who previously did several cultural activities and who went to a school with a low percentage of free/reduced lunches.
C) a student who previously did no cultural activities and who went to a school with a high percentage of free/reduced lunches.
D) a student who previously did several cultural activities and who went to a school with a high percentage of free/reduced lunches.

Accepted Answer

Kisida, Greene, and Bowen's research found that students who had fewer prior cultural experiences and who attended schools with a high percentage of free/reduced lunches benefited the most from attending the museum program. This suggests that the program was particularly effective for students from lower socioeconomic backgrounds who had less access to cultural activities.

Question 19

Which dataset did Glavin, Schieman, and Reid use for their research on work?
A) The General Social Survey
B) The National Survey of Families and Households
C) The Panel Study of Income Dynamics
D) The Work, Stress, and Health Survey

Accepted Answer

Glavin, Schieman, and Reid used the Work, Stress, and Health Survey for their research on work.

Question 20

In Glavin, Schieman, and Reid's research on work, what is the dependent variable?
A) sleep deprivation
B) hours of work
C) hours to relax
D) guilt

Accepted Answer

In Glavin, Schieman, and Reid's research on work, the dependent variable is guilt. The study focuses on how work-related factors, such as hours of work, can influence feelings of guilt, particularly in the context of balancing work and family responsibilities.

Quiz 12: Different Slopes for Different Folks: Interaction Effects

Complete this analogy: Elaboration is to interaction effects as…

Which of the following is not a reason to choose interaction over elaboration?

Let's say we're creating an interaction effect between sex and years of education. If sex is coded Male=0, Female=1, what is the value of the interaction effect for a woman with 16 years of education?

Let's say we're creating an interaction effect between sex and years of education. If sex is coded Male=0, Female=1, what is the value of the interaction effect for a man with 16 years of education?

In a regression equation that uses sex (Male=0, Female=1) , years of education, and the interaction effect between sex and education, the resulting graphs are two parallel lines. Which of the following must be true?

In a regression equation that uses sex (Male=0, Female=1) , the slope for sex has the same exact value as the interaction slope, but a different sign. What best describes the line for women?

What is the most common form of interaction effect presented in Chapter 12?

All of the interaction examples in Chapter 12 involve interacting how many parent variables?

According to the textbook examples, who is likely to have better health?

Which statement best describes the relationship between BMI and income?

In Kisida, Greene, and Bowen's research on art museums, what was the name of the art museum they studied?

What combination of methods did Kisida, Greene, and Bowen use in their research on art museums?

What behavioral measure did Kisida, Greene, and Bowen use?

According to Kisida, Greene, and Bowen's research on art museums, which type of student was most likely to benefit from attending the museum program?

Which dataset did Glavin, Schieman, and Reid use for their research on work?

In Glavin, Schieman, and Reid's research on work, what is the dependent variable?