Introduction to Mathematical Statistics |
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Page 155
... interval ( ~ – 20 / √n , x + 20 / √n ) a 95.4 per cent confidence interval for μ . The number 0.954 is called the confidence coefficient . The confidence coefficient is equal to the probability that the random interval includes the ...
... interval ( ~ – 20 / √n , x + 20 / √n ) a 95.4 per cent confidence interval for μ . The number 0.954 is called the confidence coefficient . The confidence coefficient is equal to the probability that the random interval includes the ...
Page 158
... cent confidence interval for μ1 — μ2 when the variances of the two independent normal distributions are unknown but equal . A consideration of the difficulty encountered when the unknown variances of the two independent normal ...
... cent confidence interval for μ1 — μ2 when the variances of the two independent normal distributions are unknown but equal . A consideration of the difficulty encountered when the unknown variances of the two independent normal ...
Page 162
... cent confidence interval for o / o . EXERCISES 5.14 . If 8.6 , 7.9 , 8.3 , 6.4 , 8.4 , 9.8 , 7.2 , 7.8 , 7.5 are the observed values of a random sample of ... interval estimation . 162 [ Ch . 5 Interval Estimation Bayesian Interval Estimates.
... cent confidence interval for o / o . EXERCISES 5.14 . If 8.6 , 7.9 , 8.3 , 6.4 , 8.4 , 9.8 , 7.2 , 7.8 , 7.5 are the observed values of a random sample of ... interval estimation . 162 [ Ch . 5 Interval Estimation Bayesian Interval Estimates.
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A₁ A₂ Accordingly c₁ chi-square distribution complete sufficient statistic compute conditional p.d.f. confidence interval continuous type critical region decision function defined degrees of freedom denote a random discrete type distribution function distribution having p.d.f. Equation Example EXERCISES function F(x given hypothesis H₁ independent random variables integral joint p.d.f. k₁ Let the random Let X1 Let Y₁ likelihood ratio limiting distribution marginal p.d.f. moment-generating function mutually stochastically independent noncentral normal distribution order statistics p.d.f. of Y₁ P(A₁ Poisson distribution positive integer probability density functions probability set function quadratic form random experiment random interval random sample random variables X1 respectively sample space Show significance level simple hypothesis statistic Y₁ stochastically independent random sufficient statistic t₂ theorem unbiased statistic variance o² W₁ X₁ and X2 X₂ Y₂ Z₁ zero elsewhere μ₁ μ₂ Σ Σ σ²