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Canonical correlation calculator

Find linear combinations of two X variables and two Y variables that have the strongest possible correlation.

First canonical correlation ρ₁: —

Fill in the fields above — the result is computed on this page.

Observations
—
ρ₁²
—
Second correlation ρ₂
—
ρ₂²
—
X1 weight in first function
—
X2 weight in first function
—
Y1 weight in first function
—
Y2 weight in first function
—

First pair of canonical variates

Points show the U₁ and V₁ linear-combination scores for each observation.

Canonical roots

Function Correlation ρ ρ²
Fill in the fields above — the result is computed on this page.
What do these numbers mean?
  • ρ₁ describes the strongest linear relationship between the two variable sets.
  • ρ² gives the shared variance for the corresponding pair of canonical variates.

This version accepts exactly two variables in each set. It does not calculate Wilks' significance test and rejects singular correlation matrices.

How do I use this page?
  1. Paste four series in matching observation order.
  2. Read ρ₁ and ρ₂ and their squared values.
  3. Inspect the weights and first-pair plot while considering multicollinearity.

What this page does not do: This version accepts exactly two variables in each set. It does not calculate Wilks' significance test and rejects singular correlation matrices.

Further reading

Theory — what is canonical correlation?

Canonical correlation analysis compares entire sets of variables rather than single pairs. The calculator builds a linear function U from variables X1 and X2 and a function V from variables Y1 and Y2 so that the correlation between U and V is as large as possible. A second pair of functions captures the remaining linear dimension of the relationship, independent of the first. Unlike ordinary Pearson correlation, which compares just two variables, canonical correlation compares two linear combinations of entire variable sets at once.

Frequently asked questions

How is canonical correlation different from Pearson correlation?
Pearson compares two variables; canonical correlation compares two linear combinations built from sets of variables.
Does a high ρ₁ mean every component is strongly related?
No. A specific combination of weights can produce a high result even when some individual pairs are weakly correlated.

See also

← All calculators

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