Question 1

Which of the following best describes when two variables are said to be associated?

Accepted Answer

When knowing the value of one variable helps predict, explain, or understand the value of the other variable.

Question 2

Suppose you are comparing the blood pressure of patients who lived and died in the ICU. If the median blood pressure is similar in both groups and the number of outliers is about the same, what can you conclude?

Accepted Answer

There is no association between blood pressure and survival outcome.

Question 3

Which graphical method is generally easiest to use when comparing a quantitative variable across categories of a categorical variable?

Accepted Answer

Side-by-side boxplots

Question 4

If the difference in means between two groups is large, what does this suggest?

Accepted Answer

There is likely some kind of relationship between the two variables.

Question 5

Which of the following is NOT a property of Pearson’s correlation coefficient $$r$$?

Accepted Answer

It depends on the units of the variables.

Question 6

Given a scatterplot where most points are in the upper left and lower right quadrants formed by the means of $$x$$ and $$y$$, what is the direction of the association?

Accepted Answer

Negative

Question 7

A scatterplot shows a pronounced curve rather than a straight line. Which of the following is true?

Accepted Answer

The association is nonlinear and a linear model will not be useful for predictions.

Question 8

If $$|r| = 0.8$$, how would you describe the strength of the linear association?

Accepted Answer

Strong

Question 9

Which of the following best describes a piecewise linear pattern in a scatterplot?

Accepted Answer

The rate of change is constant for one group of points and different but constant for another group.

Question 10

Suppose in a study, 22.5% of patients who died had blood pressure of 80 or less, while only 1.25% of patients who lived had blood pressure that low. What is the relative likelihood of dying for a patient with blood pressure of 80 or less?

Accepted Answer

18 times more likely to die than to live

Question 11

Which of the following statements about correlation is FALSE?

Accepted Answer

Correlation implies causation.

Question 12

If a scatterplot shows $$y$$ values scattered equally above and below the mean of $$y$$ for all $$x$$ values, what can you conclude?

Accepted Answer

There is no association between $$x$$ and $$y.$$

Question 13

Which summary statistic would you use to describe the typical value of a quantitative variable if the data are strongly skewed or have outliers?

Accepted Answer

Median

Question 14

A researcher finds $$r = -0.65$$ between hours of TV watched and exam scores. How would you describe this association?

Accepted Answer

Moderate negative linear association

Question 15

Which of the following is a correct interpretation of a positive correlation between two variables?

Accepted Answer

As one variable increases, the other variable tends to increase as well.

Question 16

If the correlation between two variables is $$r = 0$$, which of the following is true?

Accepted Answer

There is no linear association between the variables.

Question 17

Which of the following best describes the form, direction, and strength of a relationship in a scatterplot?

Accepted Answer

Form: linear or nonlinear; Direction: positive or negative; Strength: strong, moderate, or weak

Question 18

If you switch the $$x$$ and $$y$$ variables in a correlation calculation, what happens to the value of $$r$$?

Accepted Answer

It remains the same.

Question 19

Which of the following is a real-world example of a nonlinear association?

Accepted Answer

The relationship between college enrollment and faculty salary, where the scatterplot shows a pronounced curve.

Question 20

A scatterplot shows two distinct linear trends for two groups of data points. What might this indicate?

Accepted Answer

The presence of a categorical variable affecting the relationship (piecewise linear pattern).

Study Notes: Two Variable Relationships in Introductory Statistics

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