Statistical inferenceThis book offers a modern approach to statistical inference with more information on ancillarity, invariance, Bayesian methods, pivots, Stein estimation, errors in variables, and inequalities. Many ideas are introduced in the context of data analysis rather than pure mathematics. 
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Review: Statistical Inference
User Review  Fleur_de_soie  GoodreadsRead this book because it is the text for our PhD Econometrics I course, also mainly because it is recommended by Professor D, so first comes his comments on the book. "The standard PhD level first ... Read full review
Review: Statistical Inference
User Review  Cristina  GoodreadsI like how theorems and corollaries are presented, but I'm not crazy about the lack of proofs and some of the examples. This isn't a book from which I could very easily selfteach myself statistics ... Read full review
Contents
Probability Theory 1  xix 
Exercises  37 
Common Families  85 
Copyright  
16 other sections not shown
Other editions  View all
Studyguide for Statistical Inference by Casella & Berger, ISBN 9780534243128 George Casella,Roger L. Berger No preview available  2006 
Common terms and phrases
acceptance region ancillary statistic ANOVA approximation assumption Bayes estimator Bayes rule best unbiased estimator calculate confidence interval confidence set constant converges coverage probability decision rule defined definition degrees of freedom denote derived equal equation Example Exercise exponential family Find finite Fx(x given hence hypothesis testing Inequality inference integral interval estimator joint pdf Lemma level a test likelihood function Likelihood Principle linear loss function marginal distribution mean and variance method minimax NeymanPearson Lemma normal distribution observed obtain parameter pdf or pmf point estimation Poisson Poisson(A population power function probability distribution Proof properties prove random sample random vector regression reject H0 rejection region relationship risk function sample mean sample points sample space satisfies Show sufficient statistic sum of squares Suppose Theorem transformation Type I Error UMP level unbiased estimator verify versus H Xn be iid zero