## Introduction to Mathematical Statistics |

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Page 30

We observe that this p.d.f. is a

of the continuous type or of the discrete type is a

, we say that the probability is distributed uniformly over 3/. Thus, in the above ...

We observe that this p.d.f. is a

**constant**on 9/. If the p.d.f. of one or more variablesof the continuous type or of the discrete type is a

**constant**on the sample space &/, we say that the probability is distributed uniformly over 3/. Thus, in the above ...

Page 36

(a) If k is a

setting u = k and recalling that an integral (or sum) of a

is the

or ...

(a) If k is a

**constant**, then E(k) = k. This follows from expression (1) [or (2)] uponsetting u = k and recalling that an integral (or sum) of a

**constant**times a functionis the

**constant**times the integral (or sum) of the function. Of course the integral (or ...

Page 336

We then use the standard “two-sided" test of the hypothesis that pi = 12; that is, if

the computed |Tys exceeds an appropriate

pu = p 2. The

We then use the standard “two-sided" test of the hypothesis that pi = 12; that is, if

the computed |Tys exceeds an appropriate

**constant**c, we reject the hypothesispu = p 2. The

**constant**c is selected from Table IV in the Appendix to yield the ...### What people are saying - Write a review

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### Common terms and phrases

accept accordance Accordingly alternative approximately assume called cent Chapter complete compute conditional confidence interval Consider constant continuous type critical region decision defined definition degrees of freedom denote a random depend determine discrete type distribution function equal Equation event Example EXERCISES exists expected fact given Hence inequality integral interval joint p.d.f. Let X1 likelihood marginal matrix maximum mean moment-generating function mutually stochastically independent normal distribution Note observed order statistics outcome parameter Pr(X probability density functions problem proof prove random experiment random interval random sample random variable ratio reject respectively result sample space Show significance level simple hypothesis ſº stochastically independent sufficient statistic symmetric matrix Table theorem transformation true unknown variance write X1 and X2 zero elsewhere