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Linear regression and correlation coefficient

12th grade (Year 13 in England) · 16 questions · Common Core: HSS.ID.B.6, HSS.ID.C.7, HSS.ID.C.8

Name

Date

Score/ 16

  1. Question 1

    A correlation coefficient is r = 0.45. How would you describe the correlation?

    • A. strong positive
    • B. strong negative
    • C. weak positive
    • D. weak negative
    • E. no linear correlation

  2. Question 2

    The regression line is ŷ = 2.5x + 13. A data point is (7, 25.5). What is its residual (actual − predicted)?

    Answer

  3. Question 3

    A correlation coefficient is r = 0.95. How would you describe the correlation?

    • A. strong positive
    • B. strong negative
    • C. weak positive
    • D. weak negative
    • E. no linear correlation

  4. Question 4

    The regression line is ŷ = 1.5x + 2. A data point is (7, 15.5). What is its residual (actual − predicted)?

    Answer

  5. Question 5

    A correlation coefficient is r = −0.4. How would you describe the correlation?

    • A. strong positive
    • B. strong negative
    • C. weak positive
    • D. weak negative
    • E. no linear correlation

  6. Question 6

    The regression line is ŷ = 4x + 22. By how much does the predicted y change when x increases by 1?

    Answer

  7. Question 7

    A correlation coefficient is r = 0.95. How would you describe the correlation?

    • A. strong positive
    • B. strong negative
    • C. weak positive
    • D. weak negative
    • E. no linear correlation

  8. Question 8

    The regression line is ŷ = 3.5x + 19. By how much does the predicted y change when x increases by 1?

    Answer

  9. Question 9

    A correlation coefficient is r = 0.45. How would you describe the correlation?

    • A. strong positive
    • B. strong negative
    • C. weak positive
    • D. weak negative
    • E. no linear correlation

  10. Question 10

    The regression line is ŷ = 7x + 25. A data point is (5, 58). What is its residual (actual − predicted)?

    Answer

  11. Question 11

    A correlation coefficient is r = −0.4. How would you describe the correlation?

    • A. strong positive
    • B. strong negative
    • C. weak positive
    • D. weak negative
    • E. no linear correlation

  12. Question 12

    The regression line is ŷ = 1.5x − 9. A data point is (18, 16). What is its residual (actual − predicted)?

    Answer

  13. Question 13

    A correlation coefficient is r = −0.4. How would you describe the correlation?

    • A. strong positive
    • B. strong negative
    • C. weak positive
    • D. weak negative
    • E. no linear correlation

  14. Question 14

    The regression line is ŷ = 6x + 21. A data point is (8, 71). What is its residual (actual − predicted)?

    Answer

  15. Question 15

    A correlation coefficient is r = −0.92. How would you describe the correlation?

    • A. strong positive
    • B. strong negative
    • C. weak positive
    • D. weak negative
    • E. no linear correlation

  16. Question 16

    The regression line is ŷ = 4x + 24. A data point is (5, 45). What is its residual (actual − predicted)?

    Answer

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Answer key: Linear regression and correlation coefficient

  1. 1. C. weak positive

  2. 2. -5

  3. 3. A. strong positive

  4. 4. 3

  5. 5. D. weak negative

  6. 6. 4

  7. 7. A. strong positive

  8. 8. 3.5

  9. 9. C. weak positive

  10. 10. -2

  11. 11. D. weak negative

  12. 12. -2

  13. 13. D. weak negative

  14. 14. 2

  15. 15. B. strong negative

  16. 16. 1