AP Statistics : Bivariate Data
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Example Questions
Example Question #1 : Bivariate Data
Which of the following correlation coefficients indicates the strongest relationship between variables?
Correlation coefficients range from 1 to -1. The closer to either extreme, the stronger the relationship. The closer to 0, the weaker the relationship.
Example Question #2 : Bivariate Data
It is found that there is a correlation of exactly 
Correlation is measured on a scale of 
There is a strong association between the two variables.
There is enough evidence, with a correlation of 
All of the answer choices are correct
The association between the two variables is positive
There is enough evidence, with a correlation of
Under no circumstance will correlation ever equate to causation, regardless of how strong the correlation between two variables is. In this case, all other answer choices are correct.
Example Question #1 : How To Find Correlation
In a medical school, it is found that there is a correlation of 
i. There is a positive association between the two variables.
ii. There is a strong correlation between the two variables.
iii. Coffee consumption in medical school students causes students to sleep less each night.
iii only
i and ii
i, ii, and iii
i and iii
ii only
ii only
Since the correlation is negative, there must be a negative association between the two variables (therefore statement i is incorrect). Statement ii is correct since a correlation of 
Example Question #1 : How To Find Correlation
Which of the following shows the least correlation between two variables?
The strength of correlation is measured on an absolute value scale of 
A correlation of 
Example Question #1 : How To Find Correlation
Which of the following correlation coefficients implies the strongest relationship between variables:
A high correlation coefficient regardless of sign implies a stronger relationship. In this case 
Example Question #2 : Bivariate Data
A national study on cell phone use found the following correlations:
-The correlation between the number of texts sent each day and a person's average credit card debt is 
-The correlation between the number of texts sent each day and the number of books read each month is 
Which of the following statements are true?
i. As the number of texts sent each day increases, average credit card debt increases.
ii. Sending more texts causes people to read less.
iii. A person's average credit card debt is related more strongly to the number of texts sent each day than the number of books read each month is related to the number of texts sent each day.
iii
i and iii
ii
i and ii
ii and iii
i and iii
i is correct because there is a positive correlation between the number of texts sent each day and average credit card debt.
ii is incorrect because the word "cause" was used in the statement. Correlation does not mean causation. There is a relationship between the number of texts sent each day and the number of books that a person reads each month. However, the number of texts sent each day does not cause a person to read a certain number of books each month.
iii is correct because the absolute values of the correlations indicate which correlation is stronger. 
Example Question #1 : How To Find Linearity
A basketball coach wants to determine if a player's height can predict the number of points the player scores in a season. Which statistical test should the coach conduct?
Correlation
ANOVA
P-score
T-test
Linear regression
Linear regression
Linear regression is the best option for determining whether the value of one variable predicts the value of a second variable. Since that is exactly what the coach is trying to do, he should use linear regression.
Example Question #1 : How To Find The Least Squares Regression Line
In a regression analysis, the y-variable should be the ___________ variable, and the x-variable should be the ___________ variable.
Dependent, Independent
Qualified, Unqualified
Independent, Dependent
Greater, Lesser
First, Second
Dependent, Independent
Regression tests seek to determine one variable's ability to predict another variable. In this analysis, one variable is dependent (the one predicted), and the other is independent (the variable that predicts). Therefore, the dependent variable is the y-variable and the independent variable is the x-variable.
Example Question #2 : How To Find The Least Squares Regression Line
If a data set has a perfect negative linear correlation, has a slope of 
The key here is to utilize
"Perfect negative linear correlation" means 
Example Question #3 : Bivariate Data
A least-squares regression line has equation 
Use the formula 
Plug in the given values for 
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