Question 1

Sometimes, variables we are interested in researching are such that participants arrive at a study with preexisting levels of these characteristics. Accordingly, these variables cannot be experimentally manipulated. Which of the following are example(s) of variables that cannot be manipulated?

Accepted Answer

Political affiliation and openness to experience are variables that participants already possess when they arrive at a study, and they cannot be manipulated experimentally. Affective state, however, can be influenced or induced in a laboratory setting.

Question 2

Which of the following statistical analyses can be used with nonexperimental (i.e., correlational) research designs? (circle all that apply; if you choose e or f, just circle e or

Accepted Answer

Multiple regression, multilevel modeling, ANOVA, and path analysis can all be used with nonexperimental (correlational) research designs to analyze relationships between variables, account for variability, and model complex relationships without implying causation.

Question 3

Which of the following statistical analyses can be used to determine experimental causality? (circle all that apply; if you choose e or f, just circle e or

Accepted Answer

C

Question 4

Which statement best describes the term: coefficient of determination?

Accepted Answer

The coefficient of determination (also known as R-squared) represents the proportion of shared variance between two measured variables. It is a statistical measure that indicates how well the regression line (or model) fits the observed data. It ranges from 0 to 1, where a value of 1 indicates a perfect fit and a value of 0 indicates no relationship.

Question 5

The correlation between two variables in a study was extremely low, and much lower than expected (r = 0.01). Which of the following statements could be feasible explanations for the small observed relationship between X and Y?

Accepted Answer

It is possible that all of the above factors contributed to the small observed relationship between X and Y. If there is negligible systematic variation of X and Y, then it makes sense that the correlation coefficient would be close to zero. If the relationship between X and Y is curvilinear, then a linear correlation coefficient may not accurately reflect the relationship. Finally, if the range of response options on X was too narrow, then it may have been difficult to detect variation in Y based on X.

Question 6

Why does generalizing a multiple regression equation to another sample tend to produce a lower R² in the second sample?

Accepted Answer

Generalizing a regression equation assumes that the same variables are present in both sample 1 and sample 2, and that the relationships between variables are consistent across both samples. However, measurement error can affect the variables differently in each sample, which decreases the amount of correspondence between the regression weights from sample 1 and the data in sample 2. Therefore, the R² tends to be lower in the second sample.

Question 7

Two researchers wanted to investigate the relationships between the Big Five personality traits (i.e., openness to experience, conscientiousness, extroversion, agreeableness, neuroticism) and right wing authoritarianism, as well as how these factors combined to predict people's attitudes toward public schools. They conducted a survey to assess respondent's scores on these seven variables. What would be the most appropriate design to analyze these relationships?

Accepted Answer

Multiple regression is appropriate for analyzing how multiple independent variables (the Big Five traits and right-wing authoritarianism) predict a dependent variable (attitudes toward public schools).

Question 8

A correlational relationship between any two variables (A and

Accepted Answer

The answer of A correlational relationship between any two variables...

Question 9

Jesse and Hank investigated the relationships between the geographic region in which respondents lived, respondents' attitudes toward public school, and their willingness to break rules to help others, what Jesse and Hank deem the "robin hood effect." They found that in a multiple regression, with geographic region and public school attitudes as the predictors and willingness to break rules to help others as the criterion, the partial correlation between geographic location and willingness to break rules was 0.00 after controlling for public school attitudes. Conversely, after controlling for location, the partial correlation between public school attitudes and willingness to break rules was 0.50! Considering what we know about nonexperimental methods and the potential effects of error, which of the following statements is NOT a probable explanation for the observed patterns of partial correlations?

Accepted Answer

The answer of Jesse and Hank investigated the relationships between...

Question 10

Researchers wanted to investigate the relationships between number of years of school completed, whether students have had primarily male, female, or equal proportions of male and female teachers, and academic aptitude. To encompass as representative a sample as possible, researchers recruited all 6th, 9th, and 12th grade cohorts from each of 150 schools around the country. To test the effects of number of years in school and teachers' gender on scholastic aptitude, which nonexperimental research design is most appropriate?

Accepted Answer

Multilevel modeling would be the most appropriate nonexperimental research design for this study as it allows for the analysis of data that is nested at different levels (individual level and school level) and can account for the relationship between variables at each level. This design would be appropriate for examining the relationships between number of years of school completed, teacher gender, and academic aptitude while taking into account school-level effects. Multiple regression, structural equation modeling, and path analysis all have limitations for analyzing nested data and may not adequately address the hierarchical structure of the data in this study.

Question 11

In a multilevel modeling design investigating the effects of geographic location, political orientation, and whether respondents attended public or private high schools, on attitudes toward proposed environmental regulations, the observed ICC (i.e., intraclass correlation) was .95. This value suggests that:

Accepted Answer

An ICC of .95 suggests that there is substantial clustering of attitudes within geographic locations. This means that people within the same geographic location are more similar to each other in their attitudes toward proposed environmental regulations than people in different locations. Therefore, it is important for the researchers to account for the nesting of individuals within geographic locations in their analysis. Ignoring this nesting element could lead to biased results.

Question 12

A multilevel modeling design recruited people who had lived in the same city their entire lives, and investigated the effects of geographic location, political orientation, number of children, and whether respondents attended the local public or private high school (there were only two in each town), on attitudes toward proposed environmental regulations. In this example, number of children is likely a _____(a)_____ predictor of attitudes, and geographic location is likely a _____(b)_____ predictor of attitudes.

Accepted Answer

The answer of A multilevel modeling design recruited people who...

Question 13

In nonexperimental methods, which of the following designs allows the simultaneous testing of multiple predictor variables on multiple criterion variables? (circle all that apply)

Accepted Answer

Both latent structural equation models and path analysis allow the simultaneous testing of multiple predictor variables on multiple criterion variables. Multiple regression only allows for the testing of one criterion variable at a time, and multilevel modeling is primarily used to analyze data with nested structures.

Question 14

In structural equation modeling, exogenous variables __________, and endogenous variables __________. (choose the most accurate response)

Accepted Answer

Exogenous variables are those that are not predicted by any other variables in the model but predict other variables in the model. Endogenous variables are those that are predicted by other variables in the model and can also predict other variables in the model. So, option B is the most accurate response.

Question 15

In structural equation modeling, recursive models refer to _____(a)_____, and nonrecursive models refer to _____(b)_____.

Accepted Answer

Recursive models are those where causation flows in one direction without feedback loops, meaning they do not allow for bidirectional causation. Nonrecursive models, on the other hand, can include bidirectional causation or feedback loops, allowing for more complex causal relationships.

Question 16

In structural equation modeling, the path between two latent factors possesses which of the following characteristics? (circle all that apply)

Accepted Answer

The answer of In structural equation modeling, the path between...

Question 17

A study interested in gender differences in how men and women experience a treatment vs. a control would be an example of a __________. If the treatment instead was a scale assessing emotional intelligence, the study would be an example of a ____________.

Accepted Answer

A mixed factorial design involves manipulating at least two independent variables, while a nonexperimental design does not involve manipulating any variables. In the first scenario, the gender of the participants and the treatment vs. control conditions are the independent variables being manipulated, making it a mixed factorial design. In the second scenario, there is only one independent variable being used (emotional intelligence scale), so it would not be a mixed factorial design.

Question 18

The Pearson product-moment correlation:

Accepted Answer

The Pearson product-moment correlation measures the degree to which variation in one variable (X) accompanies variation in another variable (Y).

Question 19

If a Pearson's product moment correlation is obtained between two measures with Cohen's coefficient alpha values of 0.30 and 0.40, then it is likely that:

Accepted Answer

The answer of If a Pearson's product moment correlation is...

Question 20

In multiple regression equation, regression weights:

Accepted Answer

The answer of In multiple regression equation, regression weights:
...

Quiz 9: Nonexperimental Research

Sometimes, variables we are interested in researching are such that participants arrive at a study with preexisting levels of these characteristics. Accordingly, these variables cannot be experimentally manipulated. Which of the following are example(s) of variables that cannot be manipulated?

Which of the following statistical analyses can be used with nonexperimental (i.e., correlational) research designs? (circle all that apply; if you choose e or f, just circle e or

Which of the following statistical analyses can be used to determine experimental causality? (circle all that apply; if you choose e or f, just circle e or

Which statement best describes the term: coefficient of determination?

The correlation between two variables in a study was extremely low, and much lower than expected (r = 0.01) . Which of the following statements could be feasible explanations for the small observed relationship between X and Y?

Why does generalizing a multiple regression equation to another sample tend to produce a lower R² in the second sample?

A correlational relationship between any two variables (A and

In nonexperimental methods, which of the following designs allows the simultaneous testing of multiple predictor variables on multiple criterion variables? (circle all that apply)

In structural equation modeling, exogenous variables , and endogenous variables . (choose the most accurate response)

In structural equation modeling, recursive models refer to ___(a) _, and nonrecursive models refer to _(b) ___.

In structural equation modeling, the path between two latent factors possesses which of the following characteristics? (circle all that apply)

A study interested in gender differences in how men and women experience a treatment vs. a control would be an example of a . If the treatment instead was a scale assessing emotional intelligence, the study would be an example of a __.

The Pearson product-moment correlation:

If a Pearson's product moment correlation is obtained between two measures with Cohen's coefficient alpha values of 0.30 and 0.40, then it is likely that:

In multiple regression equation, regression weights:

Quiz 9: Nonexperimental Research

Sometimes, variables we are interested in researching are such that participants arrive at a study with preexisting levels of these characteristics. Accordingly, these variables cannot be experimentally manipulated. Which of the following are example(s) of variables that cannot be manipulated?

Which of the following statistical analyses can be used with nonexperimental (i.e., correlational) research designs? (circle all that apply; if you choose e or f, just circle e or

Which of the following statistical analyses can be used to determine experimental causality? (circle all that apply; if you choose e or f, just circle e or

Which statement best describes the term: coefficient of determination?

The correlation between two variables in a study was extremely low, and much lower than expected (r = 0.01) . Which of the following statements could be feasible explanations for the small observed relationship between X and Y?

Why does generalizing a multiple regression equation to another sample tend to produce a lower R2 in the second sample?

A correlational relationship between any two variables (A and

In nonexperimental methods, which of the following designs allows the simultaneous testing of multiple predictor variables on multiple criterion variables? (circle all that apply)

In structural equation modeling, exogenous variables __________, and endogenous variables __________. (choose the most accurate response)

In structural equation modeling, recursive models refer to _____(a) _____, and nonrecursive models refer to _____(b) _____.

In structural equation modeling, the path between two latent factors possesses which of the following characteristics? (circle all that apply)

A study interested in gender differences in how men and women experience a treatment vs. a control would be an example of a __________. If the treatment instead was a scale assessing emotional intelligence, the study would be an example of a ____________.

The Pearson product-moment correlation:

If a Pearson's product moment correlation is obtained between two measures with Cohen's coefficient alpha values of 0.30 and 0.40, then it is likely that:

In multiple regression equation, regression weights:

Why does generalizing a multiple regression equation to another sample tend to produce a lower R² in the second sample?

In structural equation modeling, exogenous variables , and endogenous variables . (choose the most accurate response)

In structural equation modeling, recursive models refer to ___(a) _, and nonrecursive models refer to _(b) ___.

A study interested in gender differences in how men and women experience a treatment vs. a control would be an example of a . If the treatment instead was a scale assessing emotional intelligence, the study would be an example of a __.