Regression and Residuals

Regression and Residuals

12th Grade

20 Qs

quiz-placeholder

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Regression and Residuals

Regression and Residuals

Assessment

Quiz

Mathematics

12th Grade

Hard

CCSS
8.EE.C.8C, HSF.LE.B.5, HSF-LE.A.1B

Standards-aligned

Created by

Anthony Clark

FREE Resource

20 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

50 miles

-50 miles

8 miles

-25 miles

Tags

CCSS.8.EE.C.8C

2.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

When using midterm exam scores to predict a student's final grade in the class, the student would prefer to have

positive residual, because that means the student's final grade is higher than we would predict with the model

positive residual, because that means the student's final grade is lower than we would predict with the model

residual equal to zero, because that means the student’s final grade is exactly what we would predict with the model

negative residual, because that means the student’s final grade is higher than we would predict with the model

3.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

617.51 miles

621.09 miles

100 miles

0.19 miles

Tags

CCSS.HSF.LE.B.5

4.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

We predict that for every mile driven, 61.93 hours has passed

We predict that for every mile driven, 1.79 hours has passed

We predict that for every hour driven, 1.79 miles is covered

We predict that for every hour driven, 61.93 miles is covered

Tags

CCSS.HSF.LE.B.5

5.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

A negative residual means...

that the predicted value is too big

that the predicted value is too small

that the x value is too big

that the x value is too small

Tags

CCSS.8.EE.C.8C

6.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

What is the "error" or the how off your predicted value is from your actual value?

Residual

Correlation

Causation

Error

7.

DROPDOWN QUESTION

1 min • 1 pt

Media Image

Use the dropdowns to complete the statements about the graph:

The strength of the linear relationship is ​ (a)   (strong/weak) because the residual values are relatively ​ (b)   (small/large) . The residuals on the graph ​ (c)   (show/do not show) a pattern.

weak

strong

large

small

show

do not show

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