Lesson 3-6: Analyzing Lines of Fit

Describe the correlation in the graph shown.

• Strong Negative
• Strong Positive
• Weak Negative
• Weak Positive

Tags

CCSS.HSF-LE.A.1B

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

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.IF.B.4

CCSS.HSF.IF.B.5

CCSS.HSS.ID.C.7

Is r = - 0.92 strong, moderate, or weak?

• strong

• moderate

• weak

Tags

CCSS.HSS.ID.B.5

Data is collected comparing sales of cars and the age of the salesperson. After analyzing the data, it is determined that the correlation coefficient is 0.19. What does this mean?

• There is no correlation between sales and age.

• There is a strong positive correlation between sales and age.

• There is a strong negative correlation between sales and age.

• There is a weak negative correlation between sales and age.

Tags

CCSS.HSS.ID.B.5

Determine the Correlation Coefficient (r) and decide whether it is weak, moderate, or strong.

• -0.19 weak

• -0.19 moderate

• 0.04 weak

• 0.04 strong

Tags

CCSS.HSS.ID.C.8

The scatter plot shows the number coffee shops in different cities and the number of violent crimes. Which of the following is NOT true?

• A) As the number of coffee shops increase, violent crimes appears to increase.

• B) The line of best fit (regression line) shows a positive correlation

• C) The data has a positive correlation coefficient

• D) An increase in coffee shops causes an increase in violent crimes

Tags

CCSS.HSS.ID.C.9

Estimate the correlation coefficient.

• r = -0.8
• r = -0.5
• r = 0.5
• r = 0.8

Tags

CCSS.HSS.ID.C.8