內容簡介
統計推斷原理(英文版)本書是統計學名家名作，包含9章內容和兩個附錄，前面幾章介紹一些基本概念，如參數、似然、主元等，然後介紹顯著性檢驗、漸進理論以及比較複雜的統計推斷問題。還特別介紹了實驗設計中基於隨機化的統計推斷。核心概念的解釋非常清晰，即使跳過其中的數學細節，也能使讀者理解。
本書可作為工科、管理類學科專業本科生、研究生的教材或參考書，也可供教師、工程技術人員自學之用。
圖書目錄
1Preliminaries
Summary
1.1 Starting point
1.2 Role of formal theory of inference
1.3 Some simple models
1.4 Formulation of objectives
1.5 Two broad approaches to statistical inference
1.6 Some further discussion
1.7 Parameters
Notes 1
2Some concepts and simple applications
Summary
2.1 Likelihood
2.2sufficiency
2.3 Exponential family
2.4 Choice of priors for exponential family problems
2.5 Simple frequentist discussion
2.6 Pivots
Notes 2
3Significance tests
Summary
3.1 General remarks
3.2 Simple significance test
3.3 One- and two-sided tests
3.4 Relation with acceptance and rejection
3.5 Formulation of alternatives and test statistics
3.6 Relation with interval estimation
3.7 Interpretation of significance tests
3.8 Bayesian testing
Notes 3
4More complicated situations
Summary
4.1 General remarks
4.2 General Bayesian formulation
4.3 Frequentist analysis
4.4 Some more general frequentist developments
4.5 Some further Bayesian examples
Notes 4
5Interpretations of uncertainty
Summary
5.1 General remarks
5.2 Broad roles of probability
5.3 Frequentist interpretation of upper limits
5.4 Neyman-Pearson operational criteria
5.5 Some general aspects of the frequentist approach
5.6 Yet more on the frequentist approach
5.7 Personalistic probability
5.8impersonaldegree of belief
5.9 Reference priors
5.10 Temporal coherency
5.11 Degree of belief and frequency
5.12 Statistical implementation of Bayesian analysis
5.13 Model uncertainty
5.14 Consistency of data and prior
5.15 Relevance of frequentist assessment
5.16 Sequential stopping
5.17 A simple classification problem
Notes 5
6Asymptotic theory
Summary
6.1 General remarks
6.2 Scalar parameter
……
7Further aspects of maximum likelihood
8Additional objectives
9Randomization-based analysis
