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corrected some pages
Several small corrections were done to several proofs and definitions.
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D/chi2.md

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The [probability density function of the chi-squared distribution](/P/chi2-pdf) with $k$ degrees of freedom is
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$$ \label{eq:chi2-pdf}
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\chi^{2}(x; k) = \frac{1}{2^{k/2} \, \Gamma (k/2)} \, x^{k/2-1} \, \exp \left[ -x/2 \right]
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\chi^{2}(x; k) = \frac{1}{2^{k/2} \, \Gamma (k/2)} \, x^{k/2-1} \exp \left[ -x/2 \right]
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$$
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where $k > 0$ and the density is zero, if $x \leq 0$.

P/chi2-gam.md

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**Proof:** The [probability density function of the gamma distribution](/P/gam-pdf) for $x > 0$, where $\alpha$ is the shape parameter and $\beta$ is the rate parameter, is as follows:
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$$ \label{eq:gam-pdf}
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\mathrm{Gam}(x; \alpha, \beta) = \frac{\beta^{\alpha}}{\Gamma(\alpha)} \, x^{\alpha-1} \, \exp \left[ -\beta x \right]
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\mathrm{Gam}(x; \alpha, \beta) = \frac{\beta^{\alpha}}{\Gamma(\alpha)} \, x^{\alpha-1} \exp \left[ -\beta x \right]
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$$
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If we let $\alpha = k/2$ and $\beta = 1/2$, we obtain
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$$ \label{eq:gam-pdf-chi2}
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\mathrm{Gam}\left(x; \frac{k}{2}, \frac{1}{2}\right) = \frac{x^{k/2-1} \, \exp \left[ -x/2 \right]}{\Gamma(k/2) \, 2^{k/2}} = \frac{1}{2^{k/2} \, \Gamma(k/2)} \, x^{k/2-1} \, \exp \left[ -x/2 \right]
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\mathrm{Gam}\left(x; \frac{k}{2}, \frac{1}{2}\right) = \frac{x^{k/2-1} \exp \left[ -x/2 \right]}{\Gamma(k/2) \, 2^{k/2}} = \frac{1}{2^{k/2} \, \Gamma(k/2)} \, x^{k/2-1} \exp \left[ -x/2 \right]
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$$
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which is equivalent to the [probability density function of the chi-squared distribution](/P/chi2-pdf).

P/chi2-momraw.md

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$$ \label{eq:chi2-momraw-int}
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\begin{split}
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\mathrm{E}(X^{m}) &= \int_{0}^{\infty} x^m \frac{1}{2^{k/2} \Gamma\left( \frac{k}{2} \right)} \, x^{k/2-1} \, \exp \left[ -x/2 \right] \, \mathrm{d}x \\
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&= \frac{1}{2^{k/2} \Gamma\left( \frac{k}{2} \right)} \int_{0}^{\infty} x^{(k/2)+m-1} \, \exp \left[ -x/2 \right] \, \mathrm{d}x \; .
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\mathrm{E}(X^{m}) &= \int_{0}^{\infty} x^m \frac{1}{2^{k/2} \Gamma\left( \frac{k}{2} \right)} \, x^{k/2-1} \exp \left[ -x/2 \right] \, \mathrm{d}x \\
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&= \frac{1}{2^{k/2} \Gamma\left( \frac{k}{2} \right)} \int_{0}^{\infty} x^{(k/2)+m-1} \exp \left[ -x/2 \right] \, \mathrm{d}x \; .
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\end{split}
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$$
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Now, we substitute $u = x/2$, such that $x = 2u$. As a result, we obtain:
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$$ \label{eq:chi2-momraw-int-u}
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\begin{split}
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\mathrm{E}(X^{m}) &= \frac{1}{2^{k/2} \Gamma\left( \frac{k}{2} \right)} \int_{0}^{\infty} 2^{(k/2)+m-1} \, u^{(k/2)+m-1} \, \exp[-u] \, \mathrm{d}(2u) \\
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&= \frac{2^{(k/2)+m}}{2^{k/2} \Gamma\left( \frac{k}{2} \right)} \int_{0}^{\infty} u^{(k/2)+m-1} \, \exp[-u] \, \mathrm{d}u \\
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&= \frac{2^m}{\Gamma\left( \frac{k}{2} \right)} \int_{0}^{\infty} u^{(k/2)+m-1} \, \exp[-u] \, \mathrm{d}u \; .
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\mathrm{E}(X^{m}) &= \frac{1}{2^{k/2} \Gamma\left( \frac{k}{2} \right)} \int_{0}^{\infty} 2^{(k/2)+m-1} \, u^{(k/2)+m-1} \exp[-u] \, \mathrm{d}(2u) \\
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&= \frac{2^{(k/2)+m}}{2^{k/2} \Gamma\left( \frac{k}{2} \right)} \int_{0}^{\infty} u^{(k/2)+m-1} \exp[-u] \, \mathrm{d}u \\
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&= \frac{2^m}{\Gamma\left( \frac{k}{2} \right)} \int_{0}^{\infty} u^{(k/2)+m-1} \exp[-u] \, \mathrm{d}u \; .
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\end{split}
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$$
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P/chi2-pdf.md

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Then, the [probability density function](/D/pdf) of $Y$ is
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$$ \label{eq:chi2-pdf}
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f_Y(y) = \frac{1}{2^{k/2} \, \Gamma (k/2)} \, y^{k/2-1} \, \exp \left[ -y/2 \right] \; .
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f_Y(y) = \frac{1}{2^{k/2} \, \Gamma (k/2)} \, y^{k/2-1} \exp \left[ -y/2 \right] \; .
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$$
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From this, we get the final result in \eqref{eq:chi2-pdf}:
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$$ \label{eq:y-cdf-s5}
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f_Y(y) = \frac{1}{2^{k/2} \, \Gamma (k/2)} \, y^{k/2-1} \, \exp \left[ -y/2 \right] \; .
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f_Y(y) = \frac{1}{2^{k/2} \, \Gamma (k/2)} \, y^{k/2-1} \exp \left[ -y/2 \right] \; .
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$$

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