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IB Mathematics: Applications and Interpretation SL · 13.4: Hypothesis Testing · 13.4.7

Spearman's rank correlation Problem set B Answers

Skills

  1. 0.738

  2. 0.907

    1. (a) Critic 1: 3, 5, 7, 1, 8, 4, 2, 6; Critic 2: 4, 5, 6, 2, 8, 3, 1, 7
    2. (b) 0.929
    1. (a) H0: there is no correlation between hours of sunshine and ice cream sales. H1: there is a positive correlation between hours of sunshine and ice cream sales.
    2. (b) 0.857
    3. (c) There is sufficient evidence, at the 5% significance level, of a positive correlation between hours of sunshine and ice cream sales.
    1. (a) H0: there is no correlation between days absent and exam mark. H1: there is a negative correlation between days absent and exam mark.
    2. (b) −0.905
    3. (c) There is sufficient evidence, at the 10% significance level, of a negative correlation between days absent and exam mark.

In context

    1. (a) −0.950
    2. (b) There is sufficient evidence, at the 5% significance level, of a correlation between speed and fuel economy.
    1. (a) 0.771
    2. (b) There is insufficient evidence, at the 5% significance level, that the two coaches tend to agree.
    1. (a) r_s = −0.952: strong negative correlation: people who exercise more tend to have lower blood pressure.
    2. (b) No. r_s is not exactly −1, so the ranks are not perfectly reversed: at least one person exercises more than another but has higher blood pressure. The data show a tendency, not 'always'.

Stretch

    1. (a) r increases (closer to 1)
    2. (b) r_s stays the same (0.964)
    3. (c) r_s does not change
    1. (a) 1
    2. (b) r_s measures how well the ranks agree, whatever the shape. The ranks are in exactly the same order, so r_s = 1. Pearson's r only measures straight-line correlation, and these points lie on a curve, so r < 1.

jmaths.xyz · AI SL · 13.4.7 Spearman's rank correlation