Chapter 3: Problem 13
Let \(X\) be \(b(2, p)\) and let \(Y\) be \(b(4, p)\). If \(P(X \geq 1)=\frac{5}{9}\), find \(P(Y \geq 1)\).
Chapter 3: Problem 13
Let \(X\) be \(b(2, p)\) and let \(Y\) be \(b(4, p)\). If \(P(X \geq 1)=\frac{5}{9}\), find \(P(Y \geq 1)\).
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Get started for freeLet \(Y\) have a truncated distribution with pdf \(g(y)=\phi(y)
/[\Phi(b)-\Phi(a)]\), for \(a
Let \(X\) be a random variable such that \(E\left(X^{2 m}\right)=(2 m) ! /\left(2^{m} m !\right), m=\) \(1,2,3, \ldots\) and \(E\left(X^{2 m-1}\right)=0, m=1,2,3, \ldots\) Find the mgf and the pdf of \(X\).
Let \(X\) have an exponential distribution.
(a) For \(x>0\) and \(y>0\), show that
$$
P(X>x+y \mid X>x)=P(X>y)
$$
Hence, the exponential distribution has the memoryless property. Recall from
Exercise 3.1.9 that the discrete geometric distribution has a similar
property.
(b) Let \(F(x)\) be the cdf of a continuous random variable \(Y\). Assume that
\(F(0)=0\) and \(0
Suppose \(\mathbf{X}\) has a multivariate normal distribution with mean 0 and covariance matrix $$ \boldsymbol{\Sigma}=\left[\begin{array}{llll} 283 & 215 & 277 & 208 \\ 215 & 213 & 217 & 153 \\ 277 & 217 & 336 & 236 \\ 208 & 153 & 236 & 194 \end{array}\right] $$ (a) Find the total variation of \(\mathbf{X}\). (b) Find the principal component vector Y. (c) Show that the first principal component accounts for \(90 \%\) of the total variation. (d) Show that the first principal component \(Y_{1}\) is essentially a rescaled \(\bar{X}\). Determine the variance of \((1 / 2) \bar{X}\) and compare it to that of \(Y_{1}\). Note that the \(\mathrm{R}\) command eigen(amat) obtains the spectral decomposition of the matrix amat.
Let \(f(x)\) and \(F(x)\) be the pdf and the cdf, respectively, of a distribution
of the continuous type such that \(f^{\prime}(x)\) exists for all \(x\). Let the
mean of the truncated distribution that has pdf \(g(y)=f(y) /
F(b),-\infty
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