## Introduction to mathematical statistics |

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Page 87

A random variable X which has a p.d.f. of the form of f(x) is said to have a

indicates that the Poisson p.d.f. may be used in a number of applications with

quite ...

A random variable X which has a p.d.f. of the form of f(x) is said to have a

**Poisson****distribution**, and any such f(x) is called a Poisson p.d.f. Remarks. Experienceindicates that the Poisson p.d.f. may be used in a number of applications with

quite ...

Page 89

That is, a

p.d.f. is frequently written /(X)=~F' *- 0,1.2,..., = 0 elsewhere. Thus the parameter

m in a Poisson p.d.f. is the mean /x. Table I in the Appendix gives approximately

the ...

That is, a

**Poisson distribution**has /x = a2 = m > 0. On this account, a Poissonp.d.f. is frequently written /(X)=~F' *- 0,1.2,..., = 0 elsewhere. Thus the parameter

m in a Poisson p.d.f. is the mean /x. Table I in the Appendix gives approximately

the ...

Page 194

We shall find the limiting distribution of the binomial distribution, when p = p/n, by

finding the limit of M(t; n). ... Since there exists a distribution, namely, the

We shall find the limiting distribution of the binomial distribution, when p = p/n, by

finding the limit of M(t; n). ... Since there exists a distribution, namely, the

**Poisson****distribution**with mean p, that has this moment-generating function g"<e'-1), ...### What people are saying - Write a review

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Accordingly best critical region binomial distribution cent confidence interval Chapter chi-square distribution complete sufficient statistic conditional p.d.f. confidence interval Consider continuous type converges stochastically critical region decision function defined degrees of freedom denote a random discrete type distribution having p.d.f. Equation Example EXERCISES F distribution function of Y1 given H0 is true independent random variables inequality integral joint p.d.f. Let the random Let X1 limiting distribution marginal p.d.f. matrix maximum likelihood moment-generating function mutually stochastically independent noncentral order statistics Poisson distribution positive integer power function Pr X1 probability density functions probability set function quadratic form random experiment random interval random sample random variables X1 reject H0 respectively sample space Show significance level simple hypothesis H0 statistic for 9 statistic Y1 stochastically independent random subset testing H0 theorem type of random unbiased statistic variance a2 X1 and X2 Xn denote zero elsewhere