Introduction to Mathematical StatisticsThis classic book retains its outstanding ongoing features and continues to provide readers with excellent background material necessary for a successful understanding of mathematical statistics.Chapter topics cover classical statistical inference procedures in estimation and testing, and an in-depth treatment of sufficiency and testing theory—including uniformly most powerful tests and likelihood ratios. Many illustrative examples and exercises enhance the presentation of material throughout the book.For a more complete understanding of mathematical statistics. |
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Results 1-3 of 86
Page 260
... respectively . Let us now turn to the problem of finding a confi- dence interval for the difference p1 - P2 . Let X1 , ... , Xn , be a random sample from the distribution of X and let Y1 , ... , Yn2 be a random sample from the ...
... respectively . Let us now turn to the problem of finding a confi- dence interval for the difference p1 - P2 . Let X1 , ... , Xn , be a random sample from the distribution of X and let Y1 , ... , Yn2 be a random sample from the ...
Page 285
... respectively . If from 160 independent observations the observed frequencies of these respective classifications are 86 , 35 , 26 , and 13 , are these data consistent with the Mendelian theory ? That is , test , with a = 0.01 , the ...
... respectively . If from 160 independent observations the observed frequencies of these respective classifications are 86 , 35 , 26 , and 13 , are these data consistent with the Mendelian theory ? That is , test , with a = 0.01 , the ...
Page 487
... respectively . Show that these are unbiased estimators of their respective parameters and compute var ( â ; ) , var ( ẞ ; ) , and var ( μ ) . - - - 9.5.4 . Prove that the linear functions X¿¡ – X¿ . – X .; + X .. and X .; – X ...
... respectively . Show that these are unbiased estimators of their respective parameters and compute var ( â ; ) , var ( ẞ ; ) , and var ( μ ) . - - - 9.5.4 . Prove that the linear functions X¿¡ – X¿ . – X .; + X .. and X .; – X ...
Contents
Some Elementary Statistical Inferences | 5 |
Multivariate Distributions | 73 |
Some Special Distributions | 133 |
Copyright | |
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Other editions - View all
Introduction to Mathematical Statistics Robert V. Hogg,Joseph W. McKean,Allen Thornton Craig No preview available - 2005 |
Introduction to Mathematical Statistics Robert V. Hogg,Hogg,Joseph W. McKean,Allen T. Craig No preview available - 2013 |
Common terms and phrases
approximate asymptotic Bayes bootstrap C₁ C₂ chi-square distribution compute conditional pdf confidence interval Consider continuous random variable continuous type correlation coefficient critical region defined degrees of freedom denote a random determine discrete random variable discrete type discussed equal equation Example Exercise Find Fx(x gamma distribution given H₁ Hence independent random variables inequality integral joint pdf Let the random Let X1 Let Y₁ likelihood function linear marginal pdf matrix median MVUE normal distribution observations obtain order statistics p-value P(C₁ p₁ pdf f(x pdf of Y₁ Poisson distribution Proof random sample random variables X1 random vector respectively result S-PLUS sample mean sample space sequence Show significance level subsets sufficient statistic Suppose t-distribution test statistic Theorem unbiased estimator Wilcoxon X₁ X1 and X2 Y₁ Y₂ zero elsewhere σ²