Probability density function | |||
Parameters |
ν > 0 degrees of freedom noncentrality parameter | ||
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Support | |||
see text | |||
CDF | see text | ||
Mean | see text | ||
Mode | see text | ||
Variance | see text | ||
Skewness | see text | ||
Excess kurtosis | see text |
The noncentral t-distribution generalizes Student's t-distribution using a noncentrality parameter. Whereas the central probability distribution describes how a test statistic t is distributed when the difference tested is null, the noncentral distribution describes how t is distributed when the null is false. This leads to its use in statistics, especially calculating statistical power. The noncentral t-distribution is also known as the singly noncentral t-distribution, and in addition to its primary use in statistical inference, is also used in robust modeling for data.