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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
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0.738
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0.907
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- (a) Critic 1: 3, 5, 7, 1, 8, 4, 2, 6; Critic 2: 4, 5, 6, 2, 8, 3, 1, 7
- (b) 0.929
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- (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.
- (b) 0.857
- (c) There is sufficient evidence, at the 5% significance level, of a positive correlation between hours of sunshine and ice cream sales.
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- (a) H0: there is no correlation between days absent and exam mark. H1: there is a negative correlation between days absent and exam mark.
- (b) −0.905
- (c) There is sufficient evidence, at the 10% significance level, of a negative correlation between days absent and exam mark.
In context
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- (a) −0.950
- (b) There is sufficient evidence, at the 5% significance level, of a correlation between speed and fuel economy.
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- (a) 0.771
- (b) There is insufficient evidence, at the 5% significance level, that the two coaches tend to agree.
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- (a) r_s = −0.952: strong negative correlation: people who exercise more tend to have lower blood pressure.
- (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
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- (a) r increases (closer to 1)
- (b) r_s stays the same (0.964)
- (c) r_s does not change
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- (a) 1
- (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