AP Statistics : AP Statistics
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Example Questions
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 #261 : Ap Statistics
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 and iii
i and ii
ii
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 
Example Question #1 : How To Find Outliers
Use the following five number summary to determine if there are any outliers in the data set:
Minimum:
Q1:
Median:
Q3:
Maximum:
It is not possible to determine if there are outliers based on the information given.
There is at least one outlier on the high end of the distribution and no outliers on the low end of the distribution.
There is at least one outlier on the high end of the distribution and at least one outlier on the low end of the distribution.
There is at least one outlier on the low end of the distribution and no outliers on the high end of the distribution.
There are no outliers.
There are no outliers.
An observation is an outlier if it falls more than 
Example Question #1 : How To Find Outliers
For a data set, the first quartile is 
Based on this information, a new observation can be considered an outlier if it is greater than what?
Use the 
This states that anything less than 
Thus, we want to find
Therefore, any new observation greater than 115 can be considered an outlier.
Example Question #61 : Data
You are given the following information regarding a particular data set:
Q1:
Q3:
Assume that the numbers 
One
Four
Three
None of the numbers are outliers
Two
Two
In order to find the outliers, we can use the 
Only two numbers are outside of the calculated range and therefore are outliers: 
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