Model Relationship with an Equation Using Chart and Table

A restaurant sells pizza for the prices in the data table. Calculate the linear regression equation of the data.

• y = 1.5x + 12

• y = 12x + 1.5

• y = 0.67x - 8

• y = -8x + 0.67

The chart below tracts starting salaries for health care workers since the year 2000. Using linear regression, find the equation of best fit. Round decimals to 3 places.

• y = 839.721x + 27541.812

• y = 27541.812x - 839.721

• y = 27541.812x + 839.721

• y = 839.721x - 27541.812

The scatter plot shows the relationship between the number of chapters and the total number of pages for several books.  Use the trend line to predict how many chapters would be in a book with 180 pages. 

• 12 chapters

• 15 chapters

• 18 chapters

• 21 chapters

The linear regression equation for the data is  y = 1.5x + 12.  Interpret the y-intercept of the equation.

• The y-intercept is 1.5.  It means that a pizza with 0 toppings will cost $1.50.

• The y-intercept is (0,12). It means that when there are 0 toppings then the cost of pizza is $12.

• There are 12 toppings.

• There are 12 pizzas.

The linear regression equation for the data is  y = 1.5x + 12.  Interpret the slope of the equation.

• The slope is (0, 1.5).  It means that a pizza with 0 toppings will cost $1.50.

• The slope is 1.5.  It means that it costs $1.50 per topping.

• There are 1.5 toppings.

• There are 1.5 pizzas.

The table shown is comparing a person's foot length to their height in cm. What is the regression line for this scenario?

The linear regression equation is y = 61.93x - 1.79.  Use the equation to predict how far this person will travel after 10 hours of driving.

• 10 miles

• 617.5 miles

• 0.19 miles

• 500 miles

The linear regression equation is y = 61.93x - 1.79.  According to the model, the slope can be interpreted as:

• After 0 hours of driving, they went 61.93 miles.

• They drove at a speed of 61.93 miles per hour.

• They drove 61.93 miles total.

• They drove 61.93 hours total.

Using your regression line, you predicted that someone who drove 4 hours traveled a total distance of 246 miles. What is the residual and does it indicate an over or under prediction?

• Residual = 6; Under prediction

• Residual = 6; Over prediction

• Residual = 248; Under prediction

• Residual = 248; Over prediction

Estimate the value of r:

• 0.99

• 0.05

• -0.99