Question 1

The distribution of scores on the dependent variable for a specific category of the independent variable is called
A) associated categories
B) the distribution correlation
C) the conditional distribution of Y
D) the marginal response category

Accepted Answer

The conditional distribution of Y refers to the distribution of the dependent variable (Y) for a specific category of the independent variable. This allows for analysis of how the relationship between the independent and dependent variables varies based on different levels or categories of the independent variable. Therefore, choice C is the best answer.

Question 2

If the distribution of the scores of one variable changes across the categories of another variable, the variables
A) are associated to some extent
B) are related in a way that is statistically significant
C) have a cause and effect relationship
D) are perfectly associated

Accepted Answer

If the distribution of scores of one variable changes across the categories of another variable, it suggests that the two variables may be associated to some extent. However, it does not necessarily mean that the relationship is statistically significant or that there is a cause-and-effect relationship between the two variables. Additionally, perfect association between two variables is rare in real-world data.

Question 3

If social class is a cause of a person's political ideology, then ___________ is the independent variable and ___________ is dependent.
A) class … ideology
B) ideology … class
C) person … ideology
D) information is not sufficient to tell which is independent and which dependent

Accepted Answer

The question states that social class is the cause of a person's political ideology, indicating that social class (independent variable) is influencing the person's political ideology (dependent variable). Therefore, the best choice is A.

Question 4

In a bivariate table, the categories of the dependent variable are placed in the
A) rows
B) columns
C) marginals
D) far right-hand column

Accepted Answer

In a bivariate table, the categories of the dependent variable (or response variable) are typically placed in the rows, while the categories of the independent variable (or explanatory variable) are typically placed in the columns. This allows for a clear comparison of how the dependent variable varies across different levels of the independent variable. Marginals refer to the totals at the end of each row and each column, while a far right-hand column is not typically used in bivariate tables.

Question 5

To display the effects of the X variable on the Y variable in a bivariate table when the independent variable has been arranged in the columns, compute percentages
A) within each column
B) between each column
C) within each row
D) using N as the denominator

Accepted Answer

Computing percentages within each column (also known as column percentages) helps to show the relationship between the independent variable (X) and the dependent variable (Y) within each level of the independent variable. This allows for a clearer interpretation of the strength and direction of the relationship between the variables, as well as any patterns or trends that may be present. Computing percentages between columns (option B) would compare the independent variable levels to each other, rather than examining the relationship within each level. Computing percentages within each row (option C) would be appropriate if the independent variable was arranged in the rows, rather than the columns. Using N as the denominator (option D) would simply show the raw counts of participants for each level of the independent variable, without providing any information about the relationship between the variables.

Question 6

A researcher has found a strong relationship between level of education and income and concludes that "higher levels of education cause higher income." What error has been made?
A) None, the argument is sound
B) Income is only nominal in level of measurement and education is ordinal so they cannot be causally related
C) Since these variables are continuous and interval ratio, they cannot have a causal relationship
D) By itself, association does not prove causation

Accepted Answer

The researcher has made the error of assuming a causal relationship based solely on the observed association between education and income. However, causation cannot be determined solely from correlation, and other factors (such as natural ability, family background, or opportunities) may also be contributing to both education and income levels. Therefore, the conclusion that "higher levels of education cause higher income" cannot be fully supported by the given evidence.

Question 7

Tests of significance and measures of association provide information about sample data that is
A) complimentary
B) contradictory
C) unnecessary
D) redundant

Accepted Answer

Tests of significance and measures of association are complimentary because they serve different purposes. Tests of significance determine whether the differences between groups or variables are statistically significant, while measures of association quantify the strength and direction of a relationship between variables. Together, they provide a more complete understanding of the data.

Question 8

Conventionally, each column of a bivariate table represents
A) the highest scores of each variable
B) a category of the independent variable (X)
C) a category of the dependent variable (Y)
D) the lowest scores on each variable

Accepted Answer

The answer of Conventionally, each column of a bivariate table...

Question 9

For variables measured at the ordinal and interval-ratio levels, measures of association will have a lower limit of _______ and an upper limit of ________
A) 0 … 100
B) 0 … ±1
C) 0 … 1
D) 1 … 0

Accepted Answer

Measures of association for variables at the ordinal and interval-ratio level can range from 0 (indicating no association) to ±1 (indicating a strong positive or negative association). Therefore, the best choice is B, which is the only option that includes this range.

Question 10

Tests of significance tell us if our results are non-random. To investigate the strength and direction of relationships, we must use
A) Chi square tests
B) ANOVA
C) percentages
D) measures of association

Accepted Answer

Measures of association, such as correlation coefficients or odds ratios, are used to investigate the strength and direction of relationships between variables. Tests of significance, such as chi square or ANOVA, tell us if those relationships are statistically significant or likely to be non-random. Percentages can be useful in summarizing data, but they do not provide information about the strength or direction of relationships.

Question 11

In the case of a perfect association, predictions from one variable to another can be made
A) only if variables are measured at the nominal level
B) when at least one variable is ordinal
C) without error
D) only if the relationship is positive

Accepted Answer

In a perfect association, there is no variability or error in the relationship between the variables. Therefore, predictions can be made without error. The level of measurement and direction of the relationship are not relevant in this case.

Question 12

For variables measured at the nominal level, measures of association will have a lower limit of _______ and an upper limit of _______
A) 0 … 100
B) - 1 … +1
C) 0 … 1
D) 1 … 0

Accepted Answer

Measures of association for variables measured at the nominal level are typically limited to values between 0 and 1. This is because nominal-level data typically cannot be ranked or ordered, and therefore measures of association like correlation coefficients are not appropriate. Instead, measures like phi coefficient, contingency coefficient, and Cramer's V are used, and these measures have a maximum value of 1 and a minimum value of 0.

Question 13

If variables are arranged in a bivariate table, we can see if they are associated by
A) adding their scores vertically
B) subtracting their scores horizontally
C) computing percentages in the direction of the independent variable
D) computing percentages in the direction of the dependent variable

Accepted Answer

The answer of If variables are arranged in a bivariate...

Question 14

Measures of association
A) increase our understanding of causal relationships among variables
B) provide proof of causal relationships among variables
C) enhance our ability to predict from one variable to another
D) both a and c

Accepted Answer

Measures of association do not provide proof of causal relationships, but they can increase our understanding of the relationship between variables and enhance our ability to predict from one variable to another. Therefore, option D (both a and c) is the best choice.

Question 15

Measures of association help social scientists accomplish two important goals
A) prediction and forecasting
B) understanding causation and measuring concepts
C) prediction and correlation
D) prediction and understanding causation

Accepted Answer

Measures of association are used to make predictions and to gain an understanding of causation between variables. Correlation is a type of association measure, but it only measures the strength and direction of the relationship between variables, while other measures like regression analysis can help determine causation. Therefore, the best choice is D, which includes both prediction and understanding causation as goals that can be achieved through measures of association.

Question 16

A researcher can demonstrate a strong association between gender and income. Which variable is independent?
A) gender
B) both
C) income
D) neither

Accepted Answer

In this scenario, gender is the independent variable as it is the predictor or the variable that is being manipulated to observe its effect on the dependent variable (income). The dependent variable is income as it is the variable that is being measured or observed for any changes in response to the independent variable.

Question 17

With the independent variable in the columns, the "maximum difference" is the largest difference
A) in column percents in any row
B) in row percents in any column
C) between the marginals
D) between any two cell frequencies

Accepted Answer

The answer of With the independent variable in the columns,...

Question 18

If there is an association between two variables,
A) the scores of the cases are approximately equal
B) the distributions of the scores approach normality
C) all of the scores are in the same row in the bivariate table
D) the conditional distributions of Y change

Accepted Answer

If there is an association between two variables, then the conditional distributions of Y (or whichever variable is on the y-axis) will change depending on the value of X (or whichever variable is on the x-axis). This means that there is some relationship between the two variables, even if it is not necessarily a causal relationship. Answers A, B, and C do not accurately describe an association between two variables.

Question 19

If the maximum difference is greater than 30, the relationship is
A) strong
B) moderate
C) weak
D) statistically significant

Accepted Answer

The answer of If the maximum difference is greater than...

Question 20

If the conditional distributions of Y do not change across the categories of X, any measure of association and the maximum difference would be
A) 1.00
B) 0.00
C) 0.10
D) 100

Accepted Answer

If the conditional distributions of Y do not change across the categories of X, it means that there is no association between X and Y. Therefore, any measure of association (e.g. correlation coefficient, chi-squared statistic) would be 0. The maximum difference would also be 0 since there is no difference to compare.

Quiz 11: Bivariate Association for Nominal- and Ordinal-Level Variables

The distribution of scores on the dependent variable for a specific category of the independent variable is called

If the distribution of the scores of one variable changes across the categories of another variable, the variables

If social class is a cause of a person's political ideology, then _ is the independent variable and _ is dependent.

In a bivariate table, the categories of the dependent variable are placed in the

To display the effects of the X variable on the Y variable in a bivariate table when the independent variable has been arranged in the columns, compute percentages

A researcher has found a strong relationship between level of education and income and concludes that "higher levels of education cause higher income." What error has been made?

Tests of significance and measures of association provide information about sample data that is

Conventionally, each column of a bivariate table represents

For variables measured at the ordinal and interval-ratio levels, measures of association will have a lower limit of _ and an upper limit of __

Tests of significance tell us if our results are non-random. To investigate the strength and direction of relationships, we must use

In the case of a perfect association, predictions from one variable to another can be made

For variables measured at the nominal level, measures of association will have a lower limit of _ and an upper limit of _

If variables are arranged in a bivariate table, we can see if they are associated by

Measures of association

Measures of association help social scientists accomplish two important goals

A researcher can demonstrate a strong association between gender and income. Which variable is independent?

With the independent variable in the columns, the "maximum difference" is the largest difference

If there is an association between two variables,

If the maximum difference is greater than 30, the relationship is

If the conditional distributions of Y do not change across the categories of X, any measure of association and the maximum difference would be