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Common Core HSS.ID.C.8 worksheet

High school · 16 questions · Common Core: HSS.ID.B.6, HSS.ID.C.7, HSS.ID.C.8, HSS.ID.C.9 · England: GCSE Higher Statistics, A-level Statistics

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  1. Question 1

    A data set has correlation coefficient r = 0.38. How would you describe the correlation?

    • A. Strong positive
    • B. Moderate positive
    • C. Little or no linear correlation

  2. Question 2

    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

  3. Question 3

    The regression line is ŷ = 2.5x + 5. By how much does the predicted y change when x increases by 1?

    Answer

  4. Question 4

    Ice-cream sales and sunburn cases are strongly correlated. Does this show that one causes the other?

    • A. Yes: strong correlation proves causation
    • B. No: the correlation must be a calculation error
    • C. Yes, but only if r is above 0.9
    • D. Not necessarily: a third factor, hot, sunny weather, could explain both

  5. Question 5

    A data set has correlation coefficient r = −0.95. How would you describe the correlation?

    • A. Strong negative
    • B. Moderate negative
    • C. Little or no linear correlation

  6. Question 6

    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

  7. Question 7

    The regression line is ŷ = 1.5x + 5. A data point is (15, 22.5). What is its residual (actual − predicted)?

    Answer

  8. Question 8

    Homes with more smart speakers use more electricity. Does this show that one causes the other?

    • A. Yes: strong correlation proves causation
    • B. Not necessarily: a third factor, household size and number of devices, could explain both
    • C. No: the correlation must be a calculation error
    • D. Yes, but only if r is above 0.9

  9. Question 9

    A data set has correlation coefficient r = −0.95. How would you describe the correlation?

    • A. Strong negative
    • B. Moderate negative
    • C. Little or no linear correlation

  10. Question 10

    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

  11. Question 11

    The regression line is ŷ = 8x + 3. A data point is (18, 149). What is its residual (actual − predicted)?

    Answer

  12. Question 12

    Children with bigger shoe sizes have better reading scores. Does this show that one causes the other?

    • A. Yes: strong correlation proves causation
    • B. Yes, but only if r is above 0.9
    • C. Not necessarily: a third factor, age, could explain both
    • D. No: the correlation must be a calculation error

  13. Question 13

    A data set has correlation coefficient r = 0.93. How would you describe the correlation?

    • A. Strong positive
    • B. Moderate positive
    • C. Little or no linear correlation

  14. Question 14

    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

  15. Question 15

    The regression line is ŷ = 6x + 10. A data point is (20, 128). What is its residual (actual − predicted)?

    Answer

  16. Question 16

    Homes with more smart speakers use more electricity. Does this show that one causes the other?

    • A. Yes, but only if r is above 0.9
    • B. Yes: strong correlation proves causation
    • C. No: the correlation must be a calculation error
    • D. Not necessarily: a third factor, household size and number of devices, could explain both

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Answer key: Common Core HSS.ID.C.8 worksheet

  1. 1. B. Moderate positive

  2. 2. B. strong negative

  3. 3. 2.5

  4. 4. D. Not necessarily: a third factor, hot, sunny weather, could explain both

  5. 5. A. Strong negative

  6. 6. A. strong positive

  7. 7. -5

  8. 8. B. Not necessarily: a third factor, household size and number of devices, could explain both

  9. 9. A. Strong negative

  10. 10. C. weak positive

  11. 11. 2

  12. 12. C. Not necessarily: a third factor, age, could explain both

  13. 13. A. Strong positive

  14. 14. D. weak negative

  15. 15. -2

  16. 16. D. Not necessarily: a third factor, household size and number of devices, could explain both

HSS.ID.C.8 Worksheet: Linear regression and correlation coefficient | Eurekami