AP Statistics Practice Quiz: Correlation
Written by AP Content Team, Verified for 2026 AP Exams, Last updated: May 2026
Test your understanding with short quizzes. This quiz has 16 questions to check your progress.
Question 1 of 16
All Questions (16)
A) Slope and y-intercept
B) Direction and strength
C) Cause and effect
D) Mean and standard deviation
Correct Answer: B
The correlation, r, gives the direction (positive or negative) and quantifies the strength (how close the points are to a line) of a linear association.
A) There is a very strong, positive linear association.
B) There is a calculation error.
C) The association is non-linear.
D) One variable causes the other.
Correct Answer: B
The correlation coefficient, r, must always be between -1 and 1, inclusive. A value of 1.25 is outside this valid range, indicating a mistake was made in the calculation.
A) There is no relationship of any kind between the variables.
B) There is a strong, negative association between the variables.
C) There is no linear association between the variables.
D) The relationship between the variables is perfectly linear.
Correct Answer: C
A correlation of r = 0 specifically means there is no linear association. It is possible that a non-linear relationship (e.g., a parabolic relationship) exists between the variables.
A) Eating ice cream causes people to be more susceptible to drowning.
B) An increase in drownings causes people to buy more ice cream.
C) There is a linear association between ice cream sales and drownings, but a third variable, such as temperature, is likely influencing both.
D) The correlation value is not strong enough to suggest any relationship.
Correct Answer: C
This is a classic example of the principle that correlation does not necessarily imply causation. A lurking variable, in this case, the hot weather (temperature), leads to both more ice cream sales and more people swimming (and thus more drownings).
A) It will be less than 0.7.
B) It will be greater than 0.7.
C) It will remain 0.7.
D) It will become negative.
Correct Answer: C
The correlation coefficient, r, is a unit-free measure. Changing the units of the variables (e.g., from inches to centimeters or pounds to kilograms) does not change the value of the correlation.
A) The relationship between the variables must be linear.
B) A linear model is guaranteed to be the best fit for the data.
C) There is a strong, positive linear association, but a visual inspection of the data is needed to confirm if a linear model is appropriate.
D) The relationship is weak.
Correct Answer: C
While a correlation of 0.98 indicates a very strong, positive linear association, it does not guarantee that a linear model is the most appropriate. The data could have a slight curve that is not captured by the correlation coefficient alone. A correlation coefficient close to 1 or -1 does not necessarily mean a linear model is appropriate.
A) A correlation close to -1.
B) A correlation close to 0.
C) A positive correlation.
D) A correlation with units of 'score-hours'.
Correct Answer: C
It is generally expected that as the number of hours spent studying increases, exam scores will also increase. This describes a positive association, which would be represented by a positive correlation coefficient (r > 0).
A) r = 0.75
B) r = -0.85
C) r = 0.10
D) r = -0.50
Correct Answer: B
The strength of a linear association is determined by the absolute value of the correlation coefficient. The value closest to 1 or -1 indicates the strongest relationship. |-0.85| = 0.85, which is greater than the absolute values of the other options.
A) By estimating from a hand-drawn line of best fit.
B) By using a complex formula calculated by hand.
C) By using statistical software or a graphing calculator.
D) By averaging the x and y values.
Correct Answer: C
The correlation coefficient is most commonly determined using technology. While a formula for r exists, it is complex and tedious to calculate by hand for any reasonably sized dataset.
A) r = 0.95
B) r = -0.95
C) r is approximately 0.
D) r is undefined for non-linear data.
Correct Answer: C
The correlation coefficient, r, measures the strength and direction of a linear association. For a symmetric U-shaped pattern, the negative linear trend on one side would be cancelled out by the positive linear trend on the other side, resulting in a correlation coefficient close to 0, which indicates no linear association, even though a strong non-linear relationship exists.
A) There is a strong, positive linear relationship between a car's age and its value.
B) There is a strong, negative linear relationship; as a car gets older, its value tends to decrease.
C) There is a weak, negative linear relationship between a car's age and its value.
D) A car's age causes its value to decrease.
Correct Answer: B
The negative sign indicates a negative association (as one variable increases, the other decreases). The value of -0.92 is close to -1, which indicates a strong linear relationship. The statement about causation in option D is not justified by correlation alone.
A) A correlation of r = 0.9 indicates a stronger linear association than r = -0.8.
B) If r = 0.99, the data must follow a perfectly straight line.
C) The value of r is not affected by changing the units of measurement of the variables.
D) A correlation of r = 0.5 means that as the explanatory variable increases, the response variable tends to increase.
Correct Answer: B
A correlation coefficient close to 1 or -1 does not necessarily mean a linear model is appropriate or that the data is perfectly linear. There could still be a slight curve in the data. Only a value of exactly 1 or -1 would indicate a perfect linear relationship.
A) The correlation is negative, so it implies that more parks cause more crime.
B) A strong correlation is not sufficient evidence to establish a causal link; other factors, like neighborhood wealth, could be influencing both variables.
C) The relationship is likely non-linear, so correlation is not a valid measure.
D) The correlation should have been calculated using technology to be valid.
Correct Answer: B
The principle that 'correlation does not necessarily imply causation' applies here. While there is an association, it is not proof that one variable causes the other. A lurking variable, such as the socioeconomic status of the neighborhoods, could be the true underlying cause for the observed relationship.
A) 0.88
B) 0.02
C) -0.79
D) 1.15
Correct Answer: C
The description indicates a negative association, where one variable increases as the other decreases. Therefore, the correlation coefficient, r, must be negative. Of the options provided, only -0.79 is a possible value for a negative correlation.
A) Close to 1, because both are numerical values.
B) Close to -1, because there is no logical connection.
C) Close to 0, because there is no expected linear association between the two variables.
D) Undefined, because phone numbers are not quantitative.
Correct Answer: C
There is no logical or theoretical reason to believe that a person's IQ and their phone number would have a linear relationship. When there is no discernible linear pattern or association between two variables, the correlation coefficient is expected to be close to 0.
A) The correlation is negative, which is impossible for time-based data.
B) The strength of the correlation (r = -0.95) is too weak to draw any conclusions.
C) The analyst has assumed a causal relationship from a correlation and has not considered that the data may have a non-linear pattern despite the strong r-value.
D) The correlation was likely calculated incorrectly, as this type of relationship should be positive.
Correct Answer: C
This reasoning has two key flaws covered by the provided content. First, correlation does not imply causation. It's possible that less happy people tend to spend more time on social media. Second, even with a strong r-value, a linear model may not be appropriate. Option C correctly combines these critical limitations.