Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mat...
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines.
The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
作者简介
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Larry Wasserman is Professor of Statistics at Carnegie Mellon University. He is also a member of the Center for Automated Learning and Discovery in the School of Computer Science. His research areas include nonparametric inference, asymptotic theory, causality, and applications to astrophysics, bioinformatics, and genetics. He is the 1999 winner of the Committee of Presidents o...
Larry Wasserman is Professor of Statistics at Carnegie Mellon University. He is also a member of the Center for Automated Learning and Discovery in the School of Computer Science. His research areas include nonparametric inference, asymptotic theory, causality, and applications to astrophysics, bioinformatics, and genetics. He is the 1999 winner of the Committee of Presidents of Statistical Societies Presidents' Award and the 2002 winner of the Centre de recherches mathematiques de Montreal–Statistical Society of Canada Prize in Statistics. He is Associate Editor of The Journal of the American Statistical Association and The Annals of Statistics. He is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics.
原文摘录
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Using fancy tools like neural nets, boosting and SVM without understanding basic statistics is like doing brain surgery before knowing how to use bandaid. (查看原文)
The basic problem that we study probability is:
Given a data generating process, what are the properties of the outcomes?
The basic problem of statistical inference is the inverse of probability:
Given the outcome, what can we say about the process that generated the data? (查看原文)
Springer Texts in Statistics(共113册)，
这套丛书还有
《Essentials of Stochastic Processes》《Introduction to Modeling and Analysis of Stochastic Systems》《Large Sample Techniques for Statistics》《Large Sample Techniques for Statistics》《Statistics and Finance》
等
。
这本书是《all of statistics》(http://www.amazon.com/All-Statistics-Statistical-Inference-Springer/dp/0387402721)的中文版。基于《all of statistics》的大名，得知中文版出了以后，我就很高兴地买了一本，拿到书后，按习惯从序言读起，结果第一页读到 “但是学生从哪儿...
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本书英文版错误首先不少，中文翻译也丢三落四，另外作者提供的代码有的也有很明显的bug。但是同类型的书又很少，这本够简洁。 来看看书里的“睿智”翻译，importance sampling那一章的tail probability例子 We will estimate this with importance sampling taking g to be a N...
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miner
科学出版社2008版
cool
Springer2004版
启明星
科学出版社2008版
1 有用 Wheyu 2014-12-07 15:53:21
统计学完全教程
0 有用 二十八戒 2022-04-01 21:39:42
Larry就是统计届最有极简精神的人。其他写书像裹脚布的人都应该跟Larry学学。
0 有用 小知识点 2022-02-08 21:54:39
涉及的东西比较多，反而难以把每个地方讲清楚。
1 有用 🐧 2022-01-09 22:44:18
All of anything but Statistics.
0 有用 Echovo!! 2020-08-30 03:01:43
买了本新的，再翻一遍
0 有用 飞翔的蘑菇🍄 2022-12-24 20:43:58 北京
还要刷第二遍！
0 有用 二十八戒 2022-04-01 21:39:42
Larry就是统计届最有极简精神的人。其他写书像裹脚布的人都应该跟Larry学学。
0 有用 小知识点 2022-02-08 21:54:39
涉及的东西比较多，反而难以把每个地方讲清楚。
1 有用 🐧 2022-01-09 22:44:18
All of anything but Statistics.
0 有用 Echovo!! 2020-08-30 03:01:43
买了本新的，再翻一遍