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Titlebook: All of Statistics; A Concise Course in Larry Wasserman Textbook 2004 Springer Science+Business Media, LLC, part of Springer Nature 2004 Bo

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發(fā)表于 2025-3-21 19:48:46 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱All of Statistics
期刊簡(jiǎn)稱A Concise Course in
影響因子2023Larry Wasserman
視頻videohttp://file.papertrans.cn/154/153420/153420.mp4
發(fā)行地址Provides a concise introduction to a larger number of topics than are usually included in a graduate-level mathematical statistics class
學(xué)科分類Springer Texts in Statistics
圖書(shū)封面Titlebook: All of Statistics; A Concise Course in  Larry Wasserman Textbook 2004 Springer Science+Business Media, LLC, part of Springer Nature 2004 Bo
影響因子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.?.
Pindex Textbook 2004
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Ontology-Based Multimedia Reasoning, .. The basic question is this: what can we say about the limiting behavior of a sequence of random variables .., .., ..,...? Since statistics and data mining are all about gathering data, we will naturally be interested in what happens as we gather more and more data.
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Causal Inferencesociated but the reverse is not, in general, true. Association does not necessarily imply causation. We will consider two frameworks for discussing causation. The first uses counterfactual random variables. The second, presented in the next chapter, uses directed acyclic graphs.
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發(fā)表于 2025-3-22 13:37:24 | 只看該作者
https://doi.org/10.1007/978-0-387-21736-9Bootstrapping; Mathematica; ROOT; Random variable; STATISTICA; classification; data mining; machine learnin
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978-1-4419-2322-6Springer Science+Business Media, LLC, part of Springer Nature 2004
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https://doi.org/10.1007/978-981-13-3678-2The mean, or expectation, of a random variable . is the average value of ..
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