Chapter 9: Problem 497
If \(\mathrm{f}(\mathrm{x})=1 / 4, \mathrm{x}=0,1,2,3\) is a probability mass function, find \(\mathrm{F}(\mathrm{t})\), the cumulative distribution function and sketch its graph.
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Chapter 9: Problem 497
If \(\mathrm{f}(\mathrm{x})=1 / 4, \mathrm{x}=0,1,2,3\) is a probability mass function, find \(\mathrm{F}(\mathrm{t})\), the cumulative distribution function and sketch its graph.
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Let Y be distributed with a Pareto distribution with parameters \(\mathrm{X}_{0}\) and \(\theta .\) The density function of such a random variable is: $$ \begin{aligned} \mathrm{f}(\mathrm{y})=\left(\theta \mathrm{X}_{0}^{\theta}\right) /\left(\mathrm{y}^{\theta+1}\right) & \mathrm{y}>\mathrm{X}_{0} \\ \text { with } \mathrm{X}_{0}, \theta>0 \end{aligned} $$ otherwise. What is the variance of \(\mathrm{Y}\) ?
Let \(X\) possess a Poisson distribution with mean \(\mu\), 1.e. $$ \mathrm{f}(\mathrm{X}, \mu)=\mathrm{e}^{-\mu}\left(\mu^{\mathrm{X}} / \mathrm{X} ;\right) $$ Suppose we want to test the null hypothesis \(\mathrm{H}_{0}: \mu=\mu_{0}\) against the alternative hypothesis, \(\mathrm{H}_{1}: \mu=\mu_{1}\), where \(\mu_{1}<\mu_{0}\). Find the best critical region for this test.
Suppose that you want to decide which of two equally-priced brands of light bulbs lasts longer. You choose a random sample of 100 bulbs of each brand and find that brand \(\mathrm{A}\) has sample mean of 1180 hours and sample standard deviation of 120 hours, and that brand \(\mathrm{B}\) has sample mean of 1160 hours and sample standard deviation of 40 hours. What decision should you make at the \(5 \%\) significance level?
Consider a simple random variable \(\mathrm{X}\) having just two possible values \(\operatorname{Pr}(\mathrm{X}=1)=\mathrm{p}\) and \(\operatorname{Pr}(\mathrm{X}=0)=1-\mathrm{p}\). Find the moment generating function of \(\mathrm{X}\) and \(\mathrm{E}\left(\mathrm{X}^{\mathrm{k}}\right)\) for all \(\mathrm{k}=1,2,3, \ldots\)
Let \(\mathrm{X}\) and \(\mathrm{Y}\) be jointly distributed with density function $$ \begin{array}{rlrl} \mathrm{f}(\mathrm{x}, \mathrm{y})= & 1 & 0<\mathrm{x}<1 \\ & & 0<\mathrm{y}<1 \\ & 0 & & \text { otherwise. } \end{array} $$ $$ \text { Find } \quad F(\lambda \mid X>Y)=\operatorname{Pr}(X \leq \lambda \mid X>Y) \text { . } $$
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