Back to the lesson and practice
PrintablePractice worksheet
Do it🖨️ On paper✏️ On screen
Layout1 column2 columns
Answer keyNoneAnswersWith steps
Questions10162430
LevelEasierMixedHarder
Print sizeNormalLarge print
New copyMake a new one

Free to print and copy for home or class. This link always prints the same sheet.

eurekami

Interpret correlation coefficients and avoid the causation trap

12th grade (Year 13 in England) · 16 questions · Common Core: HSS.ID.C.8, HSS.ID.C.9 · England: GCSE Higher Statistics, A-level Statistics

Name

Date

Score/ 16

  1. Question 1

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

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

  2. Question 2

    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

  3. Question 3

    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. Not necessarily: a third factor, household size and number of devices, could explain both
    • D. No: the correlation must be a calculation error

  4. Question 4

    A data set has correlation coefficient r = −0.1. How would you describe the correlation?

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

  5. Question 5

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

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

  6. Question 6

    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

  7. Question 7

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

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

  8. Question 8

    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

  9. Question 9

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

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

  10. Question 10

    A data set has correlation coefficient r = 0.05. How would you describe the correlation?

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

  11. Question 11

    Ice-cream sales and sunburn cases are strongly correlated. 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, hot, sunny weather, could explain both

  12. Question 12

    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

  13. Question 13

    Towns with more libraries have more crime. Does this show that one causes the other?

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

  14. Question 14

    A data set has correlation coefficient r = 0.05. How would you describe the correlation?

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

  15. Question 15

    Towns with more libraries have more crime. Does this show that one causes the other?

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

  16. Question 16

    A data set has correlation coefficient r = 0.71. How would you describe the correlation?

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

All done? Color in the animal! · Free from eurekami.com/math

for the adult only

Answer key: Interpret correlation coefficients and avoid the causation trap

  1. 1. A. Not necessarily: a third factor, age, could explain both

  2. 2. A. Strong negative

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

  4. 4. C. Little or no linear correlation

  5. 5. B. Not necessarily: a third factor, hot, sunny weather, could explain both

  6. 6. A. Strong positive

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

  8. 8. B. Moderate positive

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

  10. 10. C. Little or no linear correlation

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

  12. 12. B. Moderate positive

  13. 13. A. Not necessarily: a third factor, population size, could explain both

  14. 14. C. Little or no linear correlation

  15. 15. C. Not necessarily: a third factor, population size, could explain both

  16. 16. A. Strong positive