Probability and Statistics for Data Science: Math + R + Data

Matloff, Norman

Probability and Statistics for Data Science: Math + R + Data

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商品描述

This book covers "math stat"--distributions, expected value, estimation etc.--but takes the phrase "Data Science" in the title quite seriously:

 

* Real datasets are used extensively.

 

* All data analysis is supported by R coding.

 

* Includes many Data Science applications, such as PCA, mixture distributions, random graph models, Hidden Markov models, linear and logistic regression, and neural networks.

 

* Leads the student to think critically about the "how" and "why" of statistics, and to "see the big picture."

 

* Not "theorem/proof"-oriented, but concepts and models are stated in a mathematically precise manner.

 

Prerequisites are calculus, some matrix algebra, and some experience in programming.

 

Norman Matloff is a professor of computer science at the University of California, Davis, and was formerly a statistics professor there. He is on the editorial boards of the Journal of Statistical Software and The R Journal. His book Statistical Regression and Classification: From Linear Models to Machine Learning was the recipient of the Ziegel Award for the best book reviewed in Technometrics in 2017. He is a recipient of his university's Distinguished Teaching Award.

 

 

商品描述(中文翻譯)

本書涵蓋了「數理統計」——分佈、期望值、估計等等——但對於「資料科學」這個詞非常認真。本書廣泛使用真實數據集進行數據分析，並且所有的數據分析都有R編程支持。本書包含許多資料科學應用，如主成分分析（PCA）、混合分佈、隨機圖模型、隱馬爾可夫模型、線性和邏輯回歸以及神經網絡。本書引導學生批判性思考統計的「如何」和「為什麼」，並「看到整個大局」。本書不以「定理/證明」為導向，但概念和模型以數學精確的方式陳述。先修要求包括微積分、一些矩陣代數和一些編程經驗。

Norman Matloff是加州大學戴維斯分校的計算機科學教授，曾任該校統計學教授。他是《統計回歸與分類：從線性模型到機器學習》一書的作者，該書獲得了2017年《Technometrics》評論的Ziegel獎最佳書籍獎。他還是《Journal of Statistical Software》和《The R Journal》的編輯委員會成員。他是該大學杰出教學獎的獲獎者。

作者簡介

Norman Matloff is a professor of computer science at the University of California, Davis, and was formerly a statistics professor there. He is on the editorial boards of the Journal of Statistical Software and The R Journal. His book Statistical Regression and Classification: From Linear Models to Machine Learning was the recipient of the Ziegel Award for the best book reviewed in Technometrics in 2017. He is a recipient of his university's Distinguished Teaching Award.

作者簡介(中文翻譯)

Norman Matloff是加州大學戴維斯分校的計算機科學教授，曾任該校統計學教授。他是《統計軟體期刊》和《R期刊》的編輯委員會成員。他的書籍《統計回歸與分類：從線性模型到機器學習》獲得了2017年《Technometrics》評選的Ziegel獎最佳書籍獎。他也是該大學傑出教學獎的得主。

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