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- Measuring Correlation
Measuring Correlation
The product moment correlation coefficient (PMCC), r, measures the strength and direction of a linear relationship between two variables. It always lies between −1 and 1.
What you'll be able to do
- Interpret the value of r
- Know the range −1 ≤ r ≤ 1
- Distinguish strength and direction
- Read r from a calculator
What r tells you
The PMCC satisfies . Values near indicate strong linear correlation; near indicates weak or no linear correlation. The sign gives the direction.
Example 1Interpret .
Tip — r measures LINEAR correlation only — a strong curved pattern can still give small r.
Strength and direction
Sign: positive (both rise together), negative (one rises as the other falls). Magnitude: closer to 1 means stronger.
Formula recap
Common mistakes to avoid
Key takeaways
- PMCC r lies in [−1, 1].
- Sign = direction; magnitude = strength.
- r measures linear correlation only.
Test yourself
Answer a few questions, then review anything you missed.
Prefer paper? Open the written self-check
Answer each question before opening its answer. This self-check does not record a quiz score.
The PMCC always lies between:
- and
- and
- and
- and
Show answer and explanation
Answer: and
By definition.
indicates:
- strong negative correlation
- weak negative
- strong positive
- no correlation
Show answer and explanation
Answer: strong negative correlation
Near −1.
r close to 0 means:
- weak linear correlation
- strong correlation
- perfect correlation
- causation
Show answer and explanation
Answer: weak linear correlation
Little linear trend.
The sign of r gives the:
- direction
- strength
- sample size
- units
Show answer and explanation
Answer: direction
+ or −.
Correlation does NOT imply:
- causation
- a linear trend
- a value of r
- direction
Show answer and explanation
Answer: causation
Key warning.
Keep practising
Start with the quiz above to check the key ideas. You can also choose another topic from the practice library.
Related lessons
All 3 lessons- Same chapterExponential ModelsLinearising y = abˣ and y = axⁿ with logarithms.
- Same chapterHypothesis Testing for Zero CorrelationTesting the population correlation coefficient ρ.
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