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The notation for the chi-square distribution is:
${\chi}^{2}$ ~ ${\chi}_{\text{df}}^{2}$
where $\mathrm{df}=$ degrees of freedom depend on how chi-square is being used. (If you want to practice calculating chi-square probabilities then use $\mathrm{df}=n-1$ . The degrees of freedom for the three major uses are each calculated differently.)
For the ${\chi}^{2}$ distribution, the population mean is $\mu =\mathrm{df}$ and the population standard deviation is $\sigma =\sqrt{2\cdot \mathrm{df}}$ .
The random variable is shown as ${\chi}^{2}$ but may be any upper case letter.
The random variable for a chi-square distribution with $k$ degrees of freedom is the sum of $k$ independent, squared standard normal variables.
${\chi}^{2}=({Z}_{1}{)}^{2}+({Z}_{2}{)}^{2}+...+({Z}_{k}{)}^{2}$
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