Regression Concept Check

Using a random sample of 11 sandwiches at Wendy’s, we calculated a least-squares regression line using x = number of calories and y = price ($) and made the residual plot shown. Based on the residual plot, is a linear model is appropriate? Explain.

• No! There are negative residuals.

• No! The residual plot shows a curved pattern.

• Yes! There are positive and negative residuals.

• Yes! There is a nonlinear pattern in the residuals.

Tags

CCSS.HSS.ID.B.6B

Estimate the correlation coefficient for this scatterplot.

• r = 0.56

• r = -0.56

• r = 0.92

• r = -0.92

Tags

CCSS.HSS.ID.C.8

In a statistics course, a linear regression equation was computed to predict the final exam score based on the score on the first test of the term. The equation was y=25+0.7x where y is the final exam score and x is the score on the first test. George scored 80 on the first test. On the final exam George scored 85. What is the value of his residual?

• -4

• 4

• 4.5

• 5

• 81

Tags

CCSS.HSS.ID.B.6B

Which of the following is NOT TRUE based on the given least squares regression line.

• The correlation coefficient, r, is negative.

• Income is the response variable.

• The y-intercept is -242.3

• As hours increases, income increases.

Tags

CCSS.8.SP.A.3

The scatter plot shows the relationship between the number of chapters and the total number of pages for several books.  Use the least-squares line to predict how many chapters would be in a book with 180 pages. 

• 12 chapters
• 15 chapters
• 18 chapters
• 21 chapters

Data is collected on hours spent online and test score. The LSRL for the data is  $predicted\ score=93.98-4.07\left(time\right)$  . Interpret the slope.

• For each additional hour spent online, test score decreases by 4.07 points.

• For each additional hour spent online, test score increases by 4.07 points.
  

• For each additional point, time spent online decreases by 4.07.

• For each additional point, time spent online increases by 4.07.
  

Tags

CCSS.8.SP.A.3

The relationship between ages (in years) and the number of hours of sleep in one night is given by  $predicted\ sleep=10.45-0.09\left(age\right)$ . The residual for Jenny is -2.42. What does this mean?

• Jenny sleeps 2.42 hours more than predicted based on her age.

• Jenny sleeps 2.42 hours less than predicted based on her age. 

• Jenny sleeps 8.03 hours per night. 

• Jenny sleeps 2.42 hours per night.

Tags

CCSS.HSS.ID.B.6B

Describe the correlation.

• Negative correlation

• No correlation

• Positive correlation

• Constant correlation

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CCSS.HSS.ID.B.5

Extrapolation means using the line to predict sales for which of the following temperatures?

I. 16

II. 6

III. 40

• I and II

• I only

• II and III

• III only

Tags

CCSS.HSF.BF.A.2

Data is collected on hours spent online and test score. The LSRL for the data is  $predicted\ score=93.98-4.07\left(time\right)$  . Interpret  $r^2=0.72$  .

• There is a very strong positive association between time spent online and predicted score.

• 72% of the values in the data set fall on the least squares regression line. 
  

• Predicted score will vary from actual score on average by 0.72 points.

• 72% of the variability in score is accounted for by the linear model.
  

Tags

CCSS.HSS.ID.B.6B