## Introduction to mathematical statistics |

### From inside the book

Results 1-3 of 39

Page 2

this coin is an example of a

the two numbers zero and one; that is, the sample space is the collection of these

two numbers. Example 2. In the cast of one red die and one white die, let the ...

this coin is an example of a

**random experiment**in which the outcome is one ofthe two numbers zero and one; that is, the sample space is the collection of these

two numbers. Example 2. In the cast of one red die and one white die, let the ...

Page 79

That is, f(x) satisfies the conditions of being a p.d.f. of a random variable X of the

discrete type. ... Consider a

classified in but one of two mutually exclusive and exhaustive ways, say, success

or ...

That is, f(x) satisfies the conditions of being a p.d.f. of a random variable X of the

discrete type. ... Consider a

**random experiment**, the outcome of which can beclassified in but one of two mutually exclusive and exhaustive ways, say, success

or ...

Page 154

Suppose we are willing to accept as a fact that the outcome X of a

variance <72 but unknown mean p. That is, /x is some constant, but its value is

unknown.

Suppose we are willing to accept as a fact that the outcome X of a

**random****experiment**is a random variable that has a normal distribution with knownvariance <72 but unknown mean p. That is, /x is some constant, but its value is

unknown.

### What people are saying - Write a review

We haven't found any reviews in the usual places.

### Other editions - View all

### Common terms and phrases

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