Lesson 2e.08

2e.08 Understand the distinction between Spearman’s rank correlation coefficient and... Quiz: Pearson Edexcel Statistics, Unit 2

20 questions

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Lesson 2e.08, Understand the distinction between Spearman’s rank correlation coefficient and...: 20 multiple choice questions for the Pearson Edexcel GCSE Statistics (1ST0), Unit 2: Processing, representing and analysing data, written with Revision Ninja.

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The 20 questions

  1. Spearman's rank correlation coefficient is calculated using which values?

    • Squared deviations
    • Ranks of data
    • Mean differences
    • Actual raw values

  2. The product moment correlation coefficient (PMCC) relies on which values?

    • Actual data values
    • Cumulative totals
    • Frequency counts
    • Ranked data only

  3. Which coefficient is typically greater for a positive, non-linear monotonic relationship?

    • Both are equal
    • Correlation ratio
    • Spearman's coefficient
    • PMCC

  4. Both Spearman's coefficient and PMCC take values between which limits?

    • 0 and 1 only
    • -10 and 10
    • 0 and 100
    • -1 and +1

  5. What is the primary difference between PMCC and Spearman's coefficient?

    • Linear versus ranks
    • Positive versus negative
    • Mean versus median
    • Sample versus population

  6. What are both PMCC and Spearman coefficients for a perfect straight downward relationship?

    • 0
    • -1
    • 1
    • -0.5

  7. Which data arrangement produces both PMCC and Spearman values equal to 1?

    • Downward straight line
    • Upward straight line
    • Random scatter
    • Exponential curve

  8. When are PMCC and Spearman coefficients expected to be approximately equal?

    • Categorical
    • Linear and monotonic
    • Purely quadratic
    • Non-monotonic

  9. What does a monotonic relationship mean in correlation analysis?

    • Remains completely constant
    • Increases at a constant rate
    • Always changes direction
    • Consistently increases or decreases

  10. Why is Spearman's rank coefficient preferred when data contains extreme outliers?

    • It uses raw values
    • It uses ranks
    • It measures non-linearity directly
    • It removes the outliers

  11. What is implied if both PMCC and Spearman equal 0.4 for a dataset?

    • No correlation
    • Equal strength agreement
    • Perfect linear fit
    • Curved association

  12. A curved positive relationship has PMCC 0.7 and Spearman 0.9. What does this suggest?

    • No correlation
    • Stronger linear pattern
    • Perfect linear fit
    • Stronger monotonic pattern

  13. Which coefficient is generally more robust to a few extreme outliers?

    • Both equally
    • Spearman's rank correlation
    • Neither
    • PMCC

  14. Spearman's coefficient exceeds PMCC under which data condition?

    • Linear negative
    • Perfect straight line
    • Monotonic non-linear positive
    • Random scatter

  15. Which type of relationship can be missed when using the product moment correlation coefficient?

    • Linear relationship
    • Positive relationship
    • Curved relationship
    • Negative relationship

  16. PMCC is 0.2 and Spearman is 0.8 for a positive curve. What does this indicate?

    • No correlation
    • Strong linear association
    • Monotonic not linear
    • Negative correlation

  17. Which combination assesses both linear fit and rank correlation simultaneously?

    • PMCC only
    • Spearman only
    • Mean and median
    • PMCC and Spearman

  18. What does a Spearman coefficient of 1 indicate for a curved relationship?

    • Perfect linear fit
    • Perfect rank agreement
    • Zero correlation
    • Negative correlation

  19. Which coefficient is most suitable for judges' rankings of contestants?

    • PMCC
    • Spearman's rank correlation
    • The range
    • The median

  20. Which feature makes Spearman’s rank robust against extreme data values?

    • Using the mean
    • Using raw values
    • Using squared differences
    • Using ranks

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