Bluebook SAT Test Two-Variable Data: Models and Scatterplots 1

Question 1

A scatterplot shows the relationship between hours studied (x) and test score (y). The line of best fit is y = 4.2x + 52. What does the slope 4.2 represent?

Accepted Answer

For each additional hour studied, the predicted test score increases by 4.2 points

Answer

A student who studies 0 hours is predicted to score 4.2 points

Answer

The average test score is 4.2 points

Answer

For each additional test point, hours studied increase by 4.2

Question 2

The line of best fit for a dataset is y = −3x + 90. Which of the following best describes the relationship between x and y?

Accepted Answer

As x increases, y decreases

Answer

As x increases, y increases

Answer

x and y have no relationship

Answer

As x increases, y stays constant

Question 3

A scatterplot has the line of best fit y = 2.5x + 10. Using the model, what is the predicted value of y when x = 8?

Accepted Answer

30

Answer

28

Answer

32

Answer

20

Question 4

A data set about advertising spending (x, in thousands) and sales (y, in thousands) has the line of best fit y = 5x + 20. What does the y-intercept 20 represent in context?

Accepted Answer

Predicted sales when advertising spending is $0

Answer

The increase in sales for every $1,000 increase in advertising

Answer

The maximum sales achievable

Answer

The average advertising spending

Question 5

A scatterplot of temperature (x, °F) and ice cream sales (y, dollars) shows a strong positive correlation. Which value of r is most consistent with this description?

Accepted Answer

0.87

Answer

−0.87

Answer

0.05

Answer

−0.05

Question 6

The table shows values of x and y. Which type of model best fits the data: x: 1, 2, 3, 4; y: 3, 9, 27, 81?

Accepted Answer

Exponential

Answer

Linear

Answer

Quadratic

Answer

Constant

Question 7

A researcher plots data and finds the residuals are randomly scattered around zero with no pattern. What does this indicate?

Accepted Answer

The chosen model is a good fit for the data

Answer

The data has a strong negative correlation

Answer

The model is systematically overestimating y

Answer

A quadratic model would fit better