Linear regression practice

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

Tags

CCSS.8.EE.C.8C

A person travels by car.  They record their miles driven in a data table.  Calculate the linear regression equation of this data.

• y = 61.93x - 1.79
• y = -1.79x + 61.93
• y = 0.016x + 0.03
• y = 0.03x + 0.016

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

Find the equation of the line of best fit for the given data

• y = 163.41x+1.49

• y =- 163.41x+ 4.19

• y =- 4.19x+163.41

• y = 4.19x -163.41

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 0. 
• 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

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.

Tags

CCSS.HSF.LE.B.5