## Introduction to Mathematical Statistics |

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Page 255

be

number of independent times, say n, and the results observed. That is, we

consider a random sample X1, X2,..., Xn from a distribution which is n(6,100), and

we ...

be

**accepted**. To reach a decision, the random experiment is to be repeated anumber of independent times, say n, and the results observed. That is, we

consider a random sample X1, X2,..., Xn from a distribution which is n(6,100), and

we ...

Page 297

F : c2, T ~ c) leads to a correct decision, namely,

. We conclude this section with the general formulation of the decomposition of a

statistical hypothesis, and we give conditions under which the statistics used in ...

F : c2, T ~ c) leads to a correct decision, namely,

**accept**63 = 6, and reject 61 = 62. We conclude this section with the general formulation of the decomposition of a

statistical hypothesis, and we give conditions under which the statistics used in ...

Page 337

If the computed Wi < c1,

distribution n(pia, o”). If the computed W2 2 c.2, reject pi = puz = pa (and thus Ho)

and discontinue sampling. If the computed W2 < ca,

a ...

If the computed Wi < c1,

**accept**pui = puz and take a random sample from thedistribution n(pia, o”). If the computed W2 2 c.2, reject pi = puz = pa (and thus Ho)

and discontinue sampling. If the computed W2 < ca,

**accept**u1 = u2 = us and takea ...

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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