# chiSquareTest

Syntax

chiSquareTest(X, [Y])

Arguments

X is a numeric vector/matrix/table.

If X is a vector, Y is a numeric vector of the same length as X. If X isn’t a vector, Y is not needed.

Details

If X is a vector, conduct a Chi-squared goodness of fit test whether X and Y follow the same distribution.

If X is a matrix/table, conduct Pearson’s Chi-squared test on X.

Return a dictionary with the following keys:

• pValue: p-value of the test

• df: degree of freedom

• chiSquaredValue: Chi-squared test statistic

• method: either “Chi-square goodness of fit test” or “Pearson’s Chi-squared test”

Examples

Example 1. X is a vector.

\$ x=rand(10.0,50)
\$ y=rand(10.0,50)
\$ chiSquareTest(x,y);

pValue->0
df->49
chiSquaredValue->947.388015
method->Chi-square goodness of fit test

Example 2. X is a matrix.

\$ x = matrix([762, 484], [327, 239], [468, 477])
\$ x.rename!(`female`male, `Democrat`Independent`Republican)
\$ x;

Democrat

Independent

Republican

female

762

327

468

male

484

239

477

\$ chiSquareTest(x);
pValue->2.953589E-7
df->2
chiSquaredValue->30.070149
method->Pearson's Chi-squared test