Linear Regression/Line of Best Fit

Describe the correlation in the graph shown.

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

Tags

CCSS.HSF-LE.A.1B

Describe the correlation in the graph shown.

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

Tags

CCSS.HSF-LE.A.1B

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

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.7

The scatter plot below shows the number of books read by students in Mrs. Hall’s English class and their final grades. Which statement represents the best description about the line of best fit? 

• The more books students read, the lower their English grade.
• The more books students read, the higher their English grade.
• The fewer books students read, the higher their English grade. 
• No relationship exists between the number of books students read and their English grades. 

Tags

CCSS.HSF.LE.B.5

The table shown is comparing a person's foot length to their height in cm. Calculate a line of best fit.

• f(x) = 25.05x + 5.57
• f(x) = 5.57x + 25.05
• f(x) = -5.57x + 25.05
• f(x) = 5.57x - 25.05

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.7

CCSS.HSA.CED.A.2

The table shown is comparing a person's foot length to their height in cm. What is the relationship between foot length and height?

• strong; r = .99
• strong; r = .97
• weak; r = .38
• weak; r = .58

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

What kind of trend is shown from this scatter plot?

• positive correlation
• negative correlation
• none
• cannot be determind

What is the slope of the trend line?

• $1 per day
• $1 per week
• $20 per day
• $20 per week

Tags

CCSS.HSF.LE.B.5

What is the y-intercept of the trend line?

• (0, 0)
• (0, 20)
• (0, 100)

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.HSS.ID.B.6

CCSS.HSS.ID.C.7

CCSS.HSA.CED.A.2