Chapter 3: Problem 14
Let \(X\) have a Poisson distribution. If \(P(X=1)=P(X=3)\), find the mode of the distribution.
Chapter 3: Problem 14
Let \(X\) have a Poisson distribution. If \(P(X=1)=P(X=3)\), find the mode of the distribution.
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Get started for freeIf \(X\) is \(N\left(\mu, \sigma^{2}\right)\), find \(b\) so that \(P[-b<(X-\mu) / \sigma
Let \(Y_{1}, \ldots, Y_{k}\) have a Dirichlet distribution with parameters \(\alpha_{1}, \ldots, \alpha_{k}, \alpha_{k+1}\). (a) Show that \(Y_{1}\) has a beta distribution with parameters \(\alpha=\alpha_{1}\) and \(\beta=\alpha_{2}+\) \(\cdots+\alpha_{k+1}\) (b) Show that \(Y_{1}+\cdots+Y_{r}, r \leq k\), has a beta distribution with parameters \(\alpha=\alpha_{1}+\cdots+\alpha_{r}\) and \(\beta=\alpha_{r+1}+\cdots+\alpha_{k+1}\) (c) Show that \(Y_{1}+Y_{2}, Y_{3}+Y_{4}, Y_{5}, \ldots, Y_{k}, k \geq 5\), have a Dirichlet distribution with parameters \(\alpha_{1}+\alpha_{2}, \alpha_{3}+\alpha_{4}, \alpha_{5}, \ldots, \alpha_{k}, \alpha_{k+1}\) Hint: Recall the definition of \(Y_{i}\) in Example \(3.3 .6\) and use the fact that the sum of several independent gamma variables with \(\beta=1\) is a gamma variable.
The mgf of a random variable \(X\) is \(\left(\frac{2}{3}+\frac{1}{3}
e^{t}\right)^{9}\).
(a) Show that
$$
P(\mu-2 \sigma
Let the independent random variables \(X_{1}\) and \(X_{2}\) have binomial distribution with parameters \(n_{1}=3, p=\frac{2}{3}\) and \(n_{2}=4, p=\frac{1}{2}\), respectively. Compute \(P\left(X_{1}=X_{2}\right)\) Hint: List the four mutually exclusive ways that \(X_{1}=X_{2}\) and compute the probability of each.
Let \(X\) have a gamma distribution with pdf
$$
f(x)=\frac{1}{\beta^{2}} x e^{-x / \beta}, \quad 0
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