We wish to investigate the relationship between the number seeds planted in a garden and the number of fruit grown. The explanatory variable (EV) is

• The number of fruit grown

• The amount of soil in the garden

• The number of hours spent watering the plants

• The number of seeds planted

Tags

CCSS.HSS.ID.C.9

We wish to investigate the relationship between the time spent shopping and the number of items bought. The response variable (RV) is

• The number of items bought

• The number of items at the shop

• The time spent shopping

• The time spent getting to the shops

Tags

CCSS.HSS.ID.C.9

What axis does the explanatory variable go on?

• x-axis

• y-axis

What axis does the response variable go on?

• x-axis

• y-axis

Tags

CCSS.HSS.ID.B.6A

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

As shown in the table, a person's target heart rate during exercise changes as the person gets older. Use the graphing calculator to find the correlation coefficient.

• -0.999

• -0.664

• 0.998

• 1.503

Tags

CCSS.HSS.ID.C.8

The equation y = -2x + 7 models the amount of gas remaining in a lawnmower after x hours of use since it was filled. What is the meaning of the slope?

• For each hour of mowing, the mower is predicted to use 2 gallons.

• the predicted amount of gas the lawnmower can hold is 2 gallons

• For every two hours of mowing, the mower is predicted to use 7 gallons.

• The predicted amount of gas remaining after 1 hour is 2 gallons.

Tags

CCSS.HSF.LE.B.5

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.

Tags

CCSS.HSF.LE.B.5

Data was collected on the weight of a male laboratory rat for the first 25 weeks after its birth. The linear regression equation is

y= 40x+100, where x is number of weeks and y is weight in grams.

What does the y-intercept mean in context of the problem?

• The predicted weight of the rat in year one.

• The predicted weight of the rat at birth.

• The current weight of the rat.

• The average increase in the rat's weight.

Tags

CCSS.HSF.LE.B.5

If x is temperature and y is coffee sales, use the following formula to determine the coffee sales on a 34° day.

y = -60x+6443

• $4403

• $4673

• $8483

• $6443

Tags

CCSS.HSF.LE.B.5