Introduction to Mathematical Statistics |
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Page 49
... Chapters 1-6 , 8 , 13 ; Feller [ 10 ] , Chapter 1 ; Wilks [ 33 ] , Chapter 1 . 2. DISTRIBUTION THEORY : Cramér [ 8 ] , Chapters 14 , 15 ; Feller [ 10 ] , Chapter 2 ; Wilks [ 33 ] , Chapter 2 . 3. MATHEMATICAL EXPECTATION : Cramér [ 8 ] , ...
... Chapters 1-6 , 8 , 13 ; Feller [ 10 ] , Chapter 1 ; Wilks [ 33 ] , Chapter 1 . 2. DISTRIBUTION THEORY : Cramér [ 8 ] , Chapters 14 , 15 ; Feller [ 10 ] , Chapter 2 ; Wilks [ 33 ] , Chapter 2 . 3. MATHEMATICAL EXPECTATION : Cramér [ 8 ] , ...
Page 236
... Chapter 4 ; Wilks [ 33 ] , Chapter 12 . 2. COMPLETENESS : Lehmann [ 21 ] , Chapter 4 ; Lehmann and Scheffé [ 22 ] . 3. EXPONENTIAL CLASS : Koopman [ 19 ] ; Lehmann [ 21 ] , Chapter 2 ; Pitman [ 28 ] ; Rao [ 30 ] , Chapter 4 . 4 ...
... Chapter 4 ; Wilks [ 33 ] , Chapter 12 . 2. COMPLETENESS : Lehmann [ 21 ] , Chapter 4 ; Lehmann and Scheffé [ 22 ] . 3. EXPONENTIAL CLASS : Koopman [ 19 ] ; Lehmann [ 21 ] , Chapter 2 ; Pitman [ 28 ] ; Rao [ 30 ] , Chapter 4 . 4 ...
Page 365
... Chapter 24 ; Rao [ 30 ] , Chapter 2 ; Wilks [ 33 ] , Chapter 7 . 2. QUADRATIC FORMS : Carpenter [ 4 ] ; Cochran [ 5 ] ; Craig [ 6 , 7 ] ; Graybill [ 13 ] , Chapter 4 ; Hogg and Craig [ 18 ] ; Lancaster [ 20 ] . 3. DISTRIBUTION OF THE ...
... Chapter 24 ; Rao [ 30 ] , Chapter 2 ; Wilks [ 33 ] , Chapter 7 . 2. QUADRATIC FORMS : Carpenter [ 4 ] ; Cochran [ 5 ] ; Craig [ 6 , 7 ] ; Graybill [ 13 ] , Chapter 4 ; Hogg and Craig [ 18 ] ; Lancaster [ 20 ] . 3. DISTRIBUTION OF THE ...
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Common terms and phrases
A₁ A₂ Accordingly best critical region c₁ cent confidence interval chi-square distribution complete sufficient statistic compute conditional p.d.f. confidence interval Consider 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 H₁ hypothesis H independent random variables integral joint p.d.f. k₁ Let X1 Let Y₁ limiting distribution marginal p.d.f. matrix maximum likelihood moment-generating function mutually stochastically independent noncentral normal distribution order statistics p.d.f. of Y₁ P(A₁ p₁ Poisson distribution positive integer probability density functions 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 theorem unbiased statistic variance o² w₁ X₁ X₁ and X2 X₂ Y₂ Z₁ zero elsewhere μ₁ μ₂ Σ Σ