Linear Regression

Linear Regression

9th - 12th Grade

6 Qs

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Linear Regression

Linear Regression

Assessment

Quiz

Mathematics

9th - 12th Grade

Hard

CCSS
8.SP.A.3, 8.F.B.5, 8.SP.A.1

+3

Standards-aligned

Created by

Lauren Liberatore

FREE Resource

6 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

5 mins • 1 pt

Media Image
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

2.

MULTIPLE CHOICE QUESTION

5 mins • 1 pt

Media Image
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.

3.

MULTIPLE CHOICE QUESTION

15 mins • 1 pt

Media Image
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

4.

MULTIPLE CHOICE QUESTION

5 mins • 1 pt

Media Image
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

5.

MULTIPLE CHOICE QUESTION

5 mins • 1 pt

Media Image

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.8.F.B.5

CCSS.8.SP.A.1

CCSS.8.SP.A.2

CCSS.8.SP.A.3

6.

MULTIPLE CHOICE QUESTION

2 mins • 1 pt

Data was collected on the weight of a male  laboratory rat for the first 25 weeks after its birth. The linear regression equation is 
y= 40x+100, where x is number of weeks and y is weight in grams. 
What does the y-intercept mean in context of the problem?
The predicted weight of the rat in year 0. 
The predicted weight of the rat at birth. 
The current weight of the rat. 
The average increase in the rat's weight. 

Tags

CCSS.8.F.A.3

CCSS.8.F.B.4

CCSS.8.SP.A.3