Correlation
A statistical association between two variables, usually expressed as a coefficient between -1 and +1 indicating direction and strength.
Correlation measures how two variables move together. The most common coefficient describes linear association between continuous variables and ranges from -1 (perfect negative) through 0 (no linear association) to +1 (perfect positive). Rank-based coefficients handle ordinal or non-normal data. The sign gives the direction of the relationship; the absolute value gives its strength.
Correlation does not imply causation. An association can arise because one variable influences the other, because both are influenced by a confounding variable, or by chance in a small sample. Scatterplots help detect curvature and outliers that a single coefficient hides.
In a thesis, correlations often appear as a preliminary table before regression, showing which variables relate and screening for predictors that overlap heavily. When writing up, describe direction, strength, and significance, and keep causal language out of your interpretation unless your design supports it.
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