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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Contents
3 | 16 |
Unbiasedness Consistency and Limiting Distributions | 25 |
Multivariate Distributions | 73 |
Copyright | |
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Introduction to Mathematical Statistics Robert V. Hogg,Joseph W. McKean,Allen Thornton Craig No preview available - 2005 |
Common terms and phrases
approximate assume asymptotic best critical region complete sufficient statistic compute confidence interval Consider continuous random variable continuous type critical region defined definition degrees of freedom denote a random determine discussed equal equation Example Exercise Find first gamma distribution given Hence hypothesis H0 independent random variables inequality integral joint pdf joint polf Let the random Let X1 likelihood function likelihood ratio test linear matrix median MVUE noncentral normal distribution null observations obtain order statistics p-value pdf f(x pdf or pmf Poisson distribution power function probability density functions proof quadratic form random sample random variables X1 random vector respectively sample mean sample space sequence Show sign test significance level simple hypothesis sufficient statistic Suppose t-distribution t-test test statistic Theorem unbiased estimator variance versus H1 Wilcoxon X1 and X2 zero elsewhere