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BUILT-IN MATHEMATICA SYMBOL
Correlation
Correlation[v1, v2]
gives the correlation between the vectors 
and 
.
Correlation[m]
gives the correlation matrix for the matrix m.
Correlation[m1, m2]
gives the correlation matrix for the matrices 
and 
.
Correlation[dist]
gives the correlation matrix for the multivariate symbolic distribution dist.
Correlation[dist, i, j]
gives the 
correlation for the multivariate symbolic distribution dist.
Details
- Correlation[v1, v2] gives Pearson's correlation coefficient between
and 
. - The lists
and 
must be the same length. - Correlation[v1, v2] is equivalent to Covariance[v1, v2]/(StandardDeviation[v1]StandardDeviation[v2]).
- For a matrix m with
columns, Correlation[m] is a 
×
matrix of the correlations between columns of m. - For an
×
matrix 
and an 
×
matrix 
, Correlation[m1, m2] is a 
×
matrix of the correlations between columns of 
and columns of 
. - Correlation works with SparseArray objects.
- Correlation[dist, i, j] gives Covariance[dist, i, j]/(
i j), where 
is the i
component of the standard deviation of dist. - Correlation[dist] gives a correlation matrix with the
entry given by Correlation[dist, i, j].
New in 6 | Last modified in 8
