Linear Regression Unit 10 Lesson 7

A person travels by car.  They record their miles driven in a data table.  Identify the x-variable (input) of the data.

• Time (hours)
• Distance (miles)

Tags

CCSS.6.EE.C.9

A person travels by car.  They record their miles driven in a data table.  Identify the y-variable (output) of the data.

• Time (hours)
• Distance (miles)

Tags

CCSS.6.EE.C.9

The linear regression equation is y = 61.93x - 1.79.  Identify the y-intercept of the equation.

• Y-Int = 61.93
• Y-Int = -1.79
• Y-Int = (0, -1.79)
• Y-Int = (0, 61.93)

Tags

CCSS.HSF.LE.B.5

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

• After 0 hours of driving, they went -1.79 miles.
• They are driving -1.79 miles per hour.
• They drove 1.79 miles total.
• They drive 1.79 hours total.

Tags

CCSS.HSF.LE.B.5

The linear regression equation is y = 61.93x - 1.79.  Identify the slope of the equation.

• Slope = 61.93
• Slope = -1.79
• Slope = (0, -1.79)
• Slope = (0, 61.93)

Tags

CCSS.HSF.LE.B.5

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

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

Tags

CCSS.HSA.CED.A.2

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.7

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

Tags

CCSS.HSF.LE.B.5

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

• The y-intercept is (0, 12).  It means that a pizza with 0 toppings will cost 12 dollars.
• The y-intercept is 12.  It means that it costs 12 dollars per topping.
• There are 12 toppings.
• There are 12 pizzas.

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 1.5 dollars.
• The slope is 1.5.  It means that it costs 1.5 dollars per topping.
• There are 1.5 toppings.
• There are 1.5 pizzas.

Tags

CCSS.HSF.LE.B.5