Regressions

What type of correlation best describes the scatterplot shown.

• positive, weak

• positive, strong

• negative, weak

• no correlation

Tags

CCSS.HSF-LE.A.1B

What type of correlation best describes the scatter plot shown?

• positive, weak

• positive, strong

• negative, weak

• negative, strong

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

What correlation coefficient would be describe the correlation?

• 0

• -0.999

• 0.978

• 0.2

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

Which correlation coefficient best describes the correlation shown?

• 0

• -0.75

• -0.3

• 0.3

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

Which type of regression model does the scatter plot appear to show?

• linear

• exponential

• quadratic

Tags

CCSS.HSF.IF.B.4

CCSS.HSF.LE.A.1

CCSS.HSS.ID.B.6

Which type of regression model does the scatter plot appear to show?

• linear

• exponential

• quadratic

Tags

CCSS.HSS.ID.B.6

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.8.EE.C.8C

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 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

Tags

CCSS.HSF-LE.A.1B