Chapter 3: Problem 8
For the Burr distribution, show that $$ E\left(X^{k}\right)=\frac{1}{\beta^{k / \tau}} \Gamma\left(\alpha-\frac{k}{\tau}\right) \Gamma\left(\frac{k}{\tau}+1\right) / \Gamma(\alpha) $$ provided \(k<\alpha \tau\)
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Chapter 3: Problem 8
For the Burr distribution, show that $$ E\left(X^{k}\right)=\frac{1}{\beta^{k / \tau}} \Gamma\left(\alpha-\frac{k}{\tau}\right) \Gamma\left(\frac{k}{\tau}+1\right) / \Gamma(\alpha) $$ provided \(k<\alpha \tau\)
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Let \(X_{1}, X_{2}\) be two independent random variables having gamma distributions with parameters \(\alpha_{1}=3, \beta_{1}=3\) and \(\alpha_{2}=5, \beta_{2}=1\), respectively. (a) Find the mgf of \(Y=2 X_{1}+6 X_{2}\) (b) What is the distribution of \(Y ?\)
. Let \(X\) be \(N(0,1)\). Use the moment-generating-function technique to show that \(Y=X^{2}\) is \(\chi^{2}(1)\) Hint: \(\quad\) Evaluate the integral that represents \(E\left(e^{t X^{2}}\right)\) by writing \(w=x \sqrt{1-2 t}\), \(t<\frac{1}{2}\)
Let \(X_{1}\) and \(X_{2}\) be independent random variables. Let \(X_{1}\) and
\(Y=X_{1}+X_{2}\) have chi-square distributions with \(r_{1}\) and \(r\) degrees of
freedom, respectively. Here \(r_{1}
Let \(X\) be \(N(5,10)\). Find \(P\left[0.04<(X-5)^{2}<38.4\right]\).
Let \(X\) have the conditional Weibull pdf.
$$
f(x \mid \theta)=\theta \tau x^{\tau-1} e^{-\theta x^{\tau}}, \quad 0
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