Question 1

Which of the following describes a spurious relationship between X,Y,and Z?
A)X causes Z,which causes Y
B)Z causes X,which causes Y
C)Z has no effect on the relationship between X and Y
D)Z causes both X and Y

Accepted Answer

The answer of Which of the following describes a spurious...

Question 2

Which pattern of results in the partial tables would allow us to distinguish between spurious relationships and intervening relationships?
A)None,the patterns are the same.
B)For spurious relations,the partial measures of association are stronger than the bivariate measures.The opposite is true for intervening relationships.
C)For spurious relations,the partial measures of association are weaker than the bivariate measures.The opposite is true for intervening relationships.
D)In spurious relationships,the partial measures are different from each other.In intervening relations,the partial measures have the same value.

Accepted Answer

The answer of Which pattern of results in the partial...

Question 3

A measure of association for X and Y shows that the two variables are associated at -.63.After controlling for Z,the measures for the partial tables are -.33 and -.78.This pattern of outcomes would be consistent with
A)a direct relationship between X and Y.
B)a spurious relationship between X and Y and a direct relationship between X and Z.
C)interaction between X,Y,and Z.
D)an intervening relationship between X,Y,and Z.

Accepted Answer

The measure of association between X and Y is reduced from -.63 to -.33 and -.78 after controlling for Z, indicating an interaction between X, Y, and Z. This suggests that the relationship between X and Y is dependent on Z, indicating a more complex relationship than a direct or spurious relationship.

Question 4

If a researcher finds a spurious relationship between variables X and Y after controlling for Z,what would be the next step in the statistical analysis?
A)disregard Z and select a new control variable
B)incorporate Z into the analysis
C)disregard Y and select a new dependent variable
D)incorporate Z into the analysis as the new dependent variable

Accepted Answer

Incorporating Z into the analysis can help to clarify the relationship between X and Y and potentially identify any confounding factors that may be affecting the relationship. Disregarding Z or Y, or selecting new variables may not address the underlying issue and could lead to inaccurate conclusions. Incorporating Z as the new dependent variable may not be appropriate if it is not conceptually relevant to the research question.

Question 5

If a researcher finds interaction between variable X and Y after controlling for Z,what would be the next step in the statistical analysis?
A)disregard Z and select a new control variable
B)disregard X and select a new independent variable
C)disregard Y and select a new dependent variable
D)incorporate Z into the analysis

Accepted Answer

Since it has been determined that the interaction between X and Y is significant even after controlling for Z, incorporating Z into the analysis is the best choice. This will help to fully understand the relationship between all three variables and minimize any potential confounding effects. Disregarding Z or any of the other variables would not be appropriate.

Question 6

Partial gamma (G_p) A)measures the association between X and Y after removing the effects of Z. B)is the average of all gammas computed on partial tables. C)can never be lower in value than the bivariate gamma. D)is computed for each partial table separately.

Accepted Answer

Partial gamma measures the association between X and Y after controlling for the effects of a third variable Z, isolating the direct relationship between X and Y.

Question 7

Which of the following describes an intervening relationship between X,Y,and Z?
A)X causes Z,which causes Y
B)X causes Z,but neither has a relationship with Y
C)Z causes both X and Y
D)Z causes neither X nor Y

Accepted Answer

In an intervening relationship, one variable (in this case, Z) acts as a mediator between two other variables (X and Y). Choice A correctly describes this scenario where X leads to Z, which in turn causes Y, indicating that Z is the intervening variable between X and Y.

Question 8

Another term used to describe intervening relations is
A)specification.
B)interpretation.
C)direct.
D)unusual.

Accepted Answer

Intervening relations are often described as interpretations because they involve making sense of and understanding the connections between variables or factors in a given situation or phenomenon. While specification can also be related to defining or outlining variables, it does not necessarily capture the active process of interpreting relationships. Direct and unusual are not appropriate terms to describe intervening relations.

Question 9

In all partial tables,the conditional distributions of Y are the same for each value of X.In the bivariate table,the conditional distributions of Y were quite different for each value of X.This pattern
A)is mathematically impossible.
B)suggests a direct relationship between X and Y.
C)suggests a spurious relationship between X and Y.
D)suggests an interactive relationship between Z and Y.

Accepted Answer

If the conditional distributions of Y are the same for each value of X in partial tables but different in the bivariate table, it suggests that the relationship between X and Y in the bivariate table is spurious. This means that there is another variable Z that is affecting both X and Y, making it seem like there is a direct relationship between X and Y. Therefore, the best choice is C, which suggests a spurious relationship between X and Y.

Question 10

Which of the following describes an interactive relationship between X,Y,and Z?
A)X causes Z,which causes Y
B)X and Y are associated for some categories of Z but not for others
C)X and Y are associated for all categories of Z
D)X and Y are not associated for any categories of Z

Accepted Answer

B) describes an interactive relationship because it indicates that the association between X and Y changes depending on the category of Z, implying that Z modifies how X and Y relate to each other.

Question 11

If a researcher finds a direct relationship between X and Y after controlling for variable Z,what would be the next step in statistical analysis?
A)disregard Z and select another control variable to further test the relationship
B)disregard Y and select a new dependent variable
C)conduct a chi square test
D)incorporate Z as the new independent variable

Accepted Answer

After finding a direct relationship between X and Y while controlling for Z, the next step would be to disregard Z and select another control variable to further test the robustness of the relationship between X and Y.

Question 12

If we investigate a bivariate relationship by controlling for gender,which of the following would be consistent with a spurious relationship between X and Y?
A)the relationship between X and Y is the same for men and women
B)the bivariate relationship between X and Y is zero for both men and women
C)X and Y appear to be related for men but not for women
D)there are many fewer men than women

Accepted Answer

A spurious relationship is indicated when the relationship between X and Y disappears when controlling for a third variable, such as gender.

Question 13

Another term for interaction is
A)intervention.
B)spurions.
C)direct.
D)specification.

Accepted Answer

Specification is another term for interaction, especially in the context of statistical analysis, where it refers to how different variables interact with each other in a model.

Question 14

The gamma for a bivariate table is 0.42 and the partial gamma (G_p)is 0.40.This is consistent with A)interaction between the variables. B)an intervening relationship between X,Y,and Z. C)a direct relationship between X and Y. D)a spurious relationship between X and Z.

Accepted Answer

The answer of The gamma for a bivariate table is...

Question 15

A lambda computed for X and Y shows the variables to be associated at .58.After controlling for variable Z,the partial lambdas are 0.01,0.09,and 0.05,respectively.This pattern of outcomes would be taken as evidence of
A)a spurious relationship.
B)interaction.
C)an intervening relationship.
D)either a or c

Accepted Answer

The partial lambdas are all smaller than the original lambda, which suggests that the relationship between X and Y is spurious or mediated by Z.

Question 16

In an interactive relationship,the conditional distributions of Y in the partial tables would be ____ and the conditional distributions of Y in the bivariate table would be ____.
A)different from each other,different from the partial tables
B)the same,the same as the partial tables.
C)different from each other,the same as the partial tables
D)the same,the same as the partial tables

Accepted Answer

In an interactive relationship, the conditional distributions of Y in the partial tables are different from each other, and these distributions are also different from the conditional distributions of Y in the bivariate table.

Question 17

Lambda computed on a bivariate table was .34.Lambdas computed on partial tables are .32 and .35.What step should the researcher take next?
A)disregard Z and select a new control variable
B)incorporate Z into the analysis
C)conduct a chi square test to clarify results
D)recompute.These values are mathematically impossible.

Accepted Answer

The answer of Lambda computed on a bivariate table was...

Question 18

Lambda computed on a bivariate table was .34.Lambdas computed on partial tables were .02 and .05.What step should the researcher take next?
A)disregard Z and select a new control variable
B)incorporate Z into the analysis
C)disregard Y and select a new dependent variable
D)Z should become the new dependent variable

Accepted Answer

Since lambdas computed on partial tables are significantly different from the lambda computed on the bivariate table, it suggests a contingency relationship between the control variable Z and the dependent variable Y. Hence, incorporating Z into the analysis through multivariate analysis (e.g., logistic regression or chi-square analysis) would be the best step.

Question 19

The gamma for a bivariate table is 0.42 and the partial gamma (G_p)is 0.05.This is consistent with A)interaction between X and Z. B)interaction between X and Y. C)a direct relationship between X and Y. D)a spurious relationship between X and Y.

Accepted Answer

A large drop in gamma from 0.42 to 0.05 suggests that the original relationship between X and Y was spurious, likely due to the influence of a third variable Z.

Question 20

If we investigate a bivariate relationship by controlling for gender,which of the following would be consistent with an interactive relationship?
A)the relationship between X and Y is the same for men and women
B)the relationship between X and Y is zero for both men and women
C)X and Y appear to be related for men but not for women
D)there are many fewer men than women

Accepted Answer

If controlling for gender reveals that X and Y appear to be related for men but not for women, then there is an interaction effect occurring, where the relationship between X and Y depends on gender. Choices A and B suggest either no interaction or a main effect of gender, and choice D is not relevant to identifying an interaction effect.

Quiz 16: Elaborating Bivariate Tables

Which of the following describes a spurious relationship between X,Y,and Z?

Which pattern of results in the partial tables would allow us to distinguish between spurious relationships and intervening relationships?

A measure of association for X and Y shows that the two variables are associated at -.63.After controlling for Z,the measures for the partial tables are -.33 and -.78.This pattern of outcomes would be consistent with

If a researcher finds a spurious relationship between variables X and Y after controlling for Z,what would be the next step in the statistical analysis?

If a researcher finds interaction between variable X and Y after controlling for Z,what would be the next step in the statistical analysis?

Partial gamma (G_p)

Which of the following describes an intervening relationship between X,Y,and Z?

Another term used to describe intervening relations is

In all partial tables,the conditional distributions of Y are the same for each value of X.In the bivariate table,the conditional distributions of Y were quite different for each value of X.This pattern

Which of the following describes an interactive relationship between X,Y,and Z?

If a researcher finds a direct relationship between X and Y after controlling for variable Z,what would be the next step in statistical analysis?

If we investigate a bivariate relationship by controlling for gender,which of the following would be consistent with a spurious relationship between X and Y?

Another term for interaction is

The gamma for a bivariate table is 0.42 and the partial gamma (G_p) is 0.40.This is consistent with

A lambda computed for X and Y shows the variables to be associated at .58.After controlling for variable Z,the partial lambdas are 0.01,0.09,and 0.05,respectively.This pattern of outcomes would be taken as evidence of

In an interactive relationship,the conditional distributions of Y in the partial tables would be and the conditional distributions of Y in the bivariate table would be .

Lambda computed on a bivariate table was .34.Lambdas computed on partial tables are .32 and .35.What step should the researcher take next?

Lambda computed on a bivariate table was .34.Lambdas computed on partial tables were .02 and .05.What step should the researcher take next?

The gamma for a bivariate table is 0.42 and the partial gamma (G_p) is 0.05.This is consistent with

If we investigate a bivariate relationship by controlling for gender,which of the following would be consistent with an interactive relationship?