Data in a Table and Scatterplots

This scatter plot shows the average traffic volume and average vehicle speed on a certain freeway for 50 days in 1999.  Which statement best describes this relationship.

• As traffic volume increases, vehicle speed increases.

• As traffic volume increases, vehicle speed decreases.

• As traffic volume increases, vehicle speed increases at first, then decreases.

• As traffic volume increases, vehicle speed decreases at first, then increases.

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.8.EE.C.8C

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

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 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 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

Estimate the correlation coefficient for this scatterplot.

• r = -0.9

• r = 1

• r = 0.9

• r = -1

Describe the relationship between the variables.

• Strong positive correlation

• Weak positive correlation

• Strong negative correlation

• Weak negative correlation

Estimate the correlation coefficient.

• r=0

• r=-1

• r=1

• r=2