Statistics · Hypothesis testing
Chapter 1 · 3
The idea
Hypothesis testing for zero correlation
Testing whether a population has any linear correlation by comparing the sample PMCC r against a critical value from tables — choosing one- or two-tailed hypotheses on ρ, and concluding in context.
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Statistics · Hypothesis testing
Hypothesis testing for zero correlation
Testing whether a population has any linear correlation by comparing the sample PMCC r against a critical value from tables — choosing one- or two-tailed hypotheses on ρ, and concluding in context.
Why it works
Sample r vs population ρ
Ten data points, and the calculator says . Real correlation — or a phantom? Plot ten random points and they'll often drift into a loose slope by sheer luck. A sample's PMCC is only an estimate of the true correlation in the whole population, written (rho). Even when — no real correlation — a small sample can throw up a non-zero by chance. A hypothesis test asks: is the we got big enough to be convincing evidence of real correlation, or could it just be chance?Keep reading — free
The rest of the explanation, plus 3 worked examples you step through move by move.
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