H1 Correlation Coefficient
H2 Correlation Coefficient
H3 Correlation Coefficient
H4 Correlation Coefficient
H5 Correlation Coefficient
H6 Correlation Coefficient
For two variables, the formula compares the distance of each datapoint from the variable mean and uses this to tell us how closely the relationship between the variables can be fit to an imaginary line drawn through the data. This is what we mean when we say that correlations look at linear relationships.
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What is correlation?
Correlation is a statistical measure that expresses the extent to which two variables are linearly related (meaning they change together at a constant rate). It’s a common tool for describing simple relationships without making a statement about cause and effect.
How is correlation measured?
The sample correlation coefficient, r, quantifies the strength of the relationship. Correlations are also tested for statistical significance.
What are some limitations of correlation analysis?
Correlation can’t look at the presence or effect of other variables outside of the two being explored. Importantly, correlation doesn’t tell us about cause and effect. Correlation also cannot accurately describe curvilinear relationships.