Deck 13: Investigating Relationships Between Two Variables

Question 1

In the regression equation, $Y_1=?_0+?_1X_1+...+?_1$ , the "?_o" is defined as the ______________.

Answer 1

y-intercept

Question 2

Bounded measures of association like Pearson's r vary between ____ and _____.

A) 0 and 10
B) -1 and 1
C) 0 and 1
D) -10 and 10

Answer 2

-1 and 1

Question 3

What is a linear relationship?

Answer 3

In a negative linear relationship the plotted values of Y and X fall on a straight line that slopes downward from left to right. In a positive linear relationship the plotted values of Y and X fall on a straight line that slopes upward from left to right.

Question 4

Chi squared rapidly inflates with ___________ leading many analysts to use corrective measures like phi.

A) Increases in variability
B) Decreases in variability
C) Increases in sample size
D) Decreases in sample size

Question 5

A measure of _________ describes in a single number or coefficient the kind and strength of relationship between the values of two variables.

A) Association
B) Variation
C) Causation
D) Regression

Question 6

What is the difference between a positive and negative relationship?

Question 7

When the categories of the independent are arrayed across the top of the table-that is, they are the column labels-it is essential that the percentages add to ____ down the columns (these are known as column percentages).

A) 0
B) 1
C) 10
D) 100

Question 8

The linear regression equation is ________________.

Question 9

In a measure of association for ordinal variables, a pair in which both observations have the same value on one or both variables is called a _____________ pair.

A) Discordant
B) Concordant
C) Tied
D) Jumbled

Question 10

In a measure of association for ordinal variables, a pair in which one case is lower on one of the variables but higher on the other is called a _____________ pair.

A) Discordant
B) Concordant
C) Tied
D) Jumbled

Question 11

In a measure of association for ordinal variables, a pair in which one individual is higher on both variables than the other case is called a ____________ pair.

A) Discordant
B) Concordant
C) Tied
D) Jumbled

Question 12

In the regression equation $Y_1=?_0+?_1X_1+...+?_1$
the "?₁" is defined as the ______________.

Question 13

When using measures of association it is common to discuss the strength of the association. What is meant by the strength of an association?

Question 14

You can create a ____________ variable by subtracting the mean from each value and dividing the remainder by the standard deviation.

Question 15

A ____________ shows the joint or bivariate relationship between two categorized (nominal and/or ordinal) variables.

A) Regression
B) Standard error
C) Cross-tabulation
D) Confidence interval

Question 16

Kendall's tau b, Kendall's tau c, Somer's d, and Goodman and Kruskal's gamma are all measures of ________________.

A) Regression
B) Standard error
C) Slope
D) Association

Question 17

The difference between one mean and another is a(n) __________.

A)Lambda score
B)Association score
C)Inferential size
D) Effect size

Question 18

The regression coefficient tells how much ____ changes if _____ changes by one unit.

Question 19

Please define concordant and discordant pairs and ties.

Question 20

Which of the following best describes the relationship between two variables when high values of one variable are associated with high values of the other in which plotted X?Y points fall on a straight line.

A) Positive linear
B) Negative linear
C) Positive monotonic
D) Negative monotonic

Question 21

How does a regression give us the "best fit" line to summarize the relationship between two variables?

Question 22

When the difference of the means is larger, or smaller, what are the implications for tests of statistical significance?

Question 23

How would you interpret the effect of X on Y given this regression equation: Y=3.2+6.3X?

Question 24

Please explain in your own words how ANOVA can be used to test hypotheses.

Question 25

Why is cross-tabulation an appropriate choice for analyzing two variables when both are nominal or ordinal measures but not when one or both are interval or ratio measures?