## Introduction to Mathematical Statistics |

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Page 264

Since 6' and 6" are given constants, u1(X1, X2,..., Xn; 6", 8") is a statistic; and if

the p.d.f. of this statistic can be found when Ho is true, then the

of the test of Ho against H1 can be determined from this distribution. That is, o: ...

Since 6' and 6" are given constants, u1(X1, X2,..., Xn; 6", 8") is a statistic; and if

the p.d.f. of this statistic can be found when Ho is true, then the

**significance level**of the test of Ho against H1 can be determined from this distribution. That is, o: ...

Page 302

Since 15.6 × 11.1, the hypothesis P(A) = }, i = 1, 2, ..., 6, is rejected at the (

approximate) 5 per cent

from the unit interval {z; 0 < x < 1} by a random process. Let A1 = {x; 0 < a. s. 4},

A2 = {ar; } ...

Since 15.6 × 11.1, the hypothesis P(A) = }, i = 1, 2, ..., 6, is rejected at the (

approximate) 5 per cent

**significance level**. Example 2. A point is to be selectedfrom the unit interval {z; 0 < x < 1} by a random process. Let A1 = {x; 0 < a. s. 4},

A2 = {ar; } ...

Page 338

pub, implies that the

means is b – 1 a = 1 — II (1 – c.1). i = 1 This means that, if p 1 = u2 is rejected,

using W1, at

pub, implies that the

**significance level**of this sequence of tests of the equality ofmeans is b – 1 a = 1 — II (1 – c.1). i = 1 This means that, if p 1 = u2 is rejected,

using W1, at

**significance level**al, then Ho: p1 = u2 = . . . = p, is rejected, not at ...### What people are saying - Write a review

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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