Statistical Inference
暫譯: 統計推論
Casella, George, Berger, Roger
- 出版商: CRC
- 出版日期: 2024-05-23
- 售價: $3,950
- 貴賓價: 9.5 折 $3,753
- 語言: 英文
- 頁數: 535
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1032593032
- ISBN-13: 9781032593036
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相關分類:
機率統計學 Probability-and-statistics
海外代購書籍(需單獨結帳)
相關主題
商品描述
This classic textbook builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and natural extensions, and consequences, of previous concepts. It covers all topics from a standard inference course including: distributions, random variables, data reduction, point estimation, hypothesis testing, and interval estimation.
Features
- The classic graduate-level textbook on statistical inference
- Develops elements of statistical theory from first principles of probability
- Written in a lucid style accessible to anyone with some background in calculus
- Covers all key topics of a standard course in inference
- Hundreds of examples throughout to aid understanding
- Each chapter includes an extensive set of graduated exercises
Statistical Inference, Second Edition is primarily aimed at graduate students of statistics, but can be used by advanced undergraduate students majoring in statistics who have a solid mathematics background. It also stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures, while less focused on formal optimality considerations.
This is a reprint of the second edition originally published by Cengage Learning, Inc. in 2001.
商品描述(中文翻譯)
這本經典教科書從概率論的基本原理建立理論統計。從概率的基本概念開始，作者使用統計的技術、定義和概念，發展統計推斷的理論，這些都是先前概念的自然延伸和結果。它涵蓋了標準推斷課程中的所有主題，包括：分佈、隨機變數、數據簡化、點估計、假設檢驗和區間估計。
**特色**
- 經典的研究生級統計推斷教科書
- 從概率的基本原理發展統計理論的要素
- 以清晰的風格撰寫，適合具有微積分背景的任何人
- 涵蓋標準推斷課程的所有關鍵主題
- 內含數百個例子以幫助理解
- 每章包括一套廣泛的漸進練習題
**《統計推斷（第二版）》** 主要針對統計研究生，但也可供具有堅實數學背景的高年級本科統計專業學生使用。它還強調統計理論的更實用用途，更關注於理解基本統計概念和推導合理的統計程序，而較少關注於正式的最優性考量。
這是2001年由Cengage Learning, Inc.首次出版的第二版的重印本。
作者簡介
Professor George Casella completed his undergraduate education at Fordham University and graduate education at Purdue University. He served on the faculty of Rutgers University, Cornell University, and the University of Florida. His contributions focused on the area of statistics including Monte Carlo methods, model selection, and genomic analysis. He was particularly active in Bayesian and empirical Bayes methods, with works connecting with the Stein phenomenon, on assessing and accelerating the convergence of Markov chain Monte Carlo methods, as in his Rao-Blackwellisation technique, and recasting lasso as Bayesian posterior mode estimation with independent Laplace priors.
Casella was named as a Fellow of the American Statistical Association and the Institute of Mathematical Statistics in 1988, and he was made an Elected Fellow of the International Statistical Institute in 1989. In 2009, he was made a Foreign Member of the Spanish Royal Academy of Sciences.
After receiving his doctorate in statistics from Purdue University, Professor Roger Berger held academic positions at Florida State University and North Carolina State University. He also spent two years with the National Science Foundation before coming to Arizona State University in 2004. Berger is co-author of the textbook "Statistical Inference," now in its second edition. This book has been translated into Chinese and Portuguese. His articles have appeared in publications including Journal of the American Statistical Association, Statistical Science, Biometrics and Statistical Methods in Medical Research. Berger's areas of expertise include hypothesis testing, (bio)equivalence, generalized linear models, biostatistics, and statistics education.
Berger was named as a Fellow of the American Statistical Association and the Institute of Mathematical Statistics.
作者簡介(中文翻譯)
喬治·卡塞拉教授在福坦莫大學完成了本科教育，並在普渡大學完成了研究生教育。他曾在羅格斯大學、康奈爾大學和佛羅里達大學任教。他的研究貢獻集中在統計學領域，包括蒙地卡羅方法、模型選擇和基因組分析。他特別活躍於貝葉斯和經驗貝葉斯方法，並在與斯坦現象相關的研究中，評估和加速馬可夫鏈蒙地卡羅方法的收斂，例如他的拉奧-布萊克威爾化技術，以及將套索重構為具有獨立拉普拉斯先驗的貝葉斯後驗模式估計。
卡塞拉於1988年被任命為美國統計協會和數學統計學會的會士，並於1989年成為國際統計學會的當選會士。2009年，他被任命為西班牙皇家科學院的外籍成員。
在普渡大學獲得統計學博士學位後，羅傑·伯傑教授曾在佛羅里達州立大學和北卡羅來納州立大學擔任學術職位。他還在國家科學基金會工作了兩年，然後於2004年來到亞利桑那州立大學。伯傑是教科書《統計推斷》的共同作者，該書目前已進入第二版，並已翻譯成中文和葡萄牙文。他的文章發表在《美國統計協會期刊》、《統計科學》、《生物統計學》和《醫學研究中的統計方法》等期刊上。伯傑的專業領域包括假設檢驗、（生物）等效性、廣義線性模型、生物統計學和統計教育。
伯傑被任命為美國統計協會和數學統計學會的會士。
