{"product_id":"probability-and-statistics-for-data-science-math-r-data-paperback","title":"Probability and Statistics for Data Science: Math + R + Data - Paperback","description":"\u003cp\u003eby \u003cb\u003eNorman Matloff\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eProbability and Statistics for Data Science: Math + R + Data\u003c\/strong\u003e covers \"math stat\"--distributions, expected value, estimation etc.--but takes the phrase \"Data Science\" in the title quite seriously: \u003c\/p\u003e\u003cp\u003e* Real datasets are used extensively. \u003c\/p\u003e\u003cp\u003e* All data analysis is supported by R coding. \u003c\/p\u003e\u003cp\u003e* Includes many Data Science applications, such as PCA, mixture distributions, random graph models, Hidden Markov models, linear and logistic regression, and neural networks.\u003c\/p\u003e\u003cp\u003e* Leads the student to think critically about the \"how\" and \"why\" of statistics, and to \"see the big picture.\"\u003c\/p\u003e\u003cp\u003e* Not \"theorem\/proof\"-oriented, but concepts and models are stated in a mathematically precise manner.\u003c\/p\u003e\u003cp\u003ePrerequisites are calculus, some matrix algebra, and some experience in programming.\u003c\/p\u003e\u003cp\u003eNorman 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 \u003ci\u003eJournal of Statistical Software \u003c\/i\u003eand \u003ci\u003eThe R Journal\u003c\/i\u003e. His book \u003ci\u003eStatistical Regression and Classification: From Linear Models to Machine Learning\u003c\/i\u003e was the recipient of the Ziegel Award for the best book reviewed in \u003ci\u003eTechnometrics\u003c\/i\u003e in 2017. He is a recipient of his university's Distinguished Teaching Award.\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eNorman Matloff\u003c\/strong\u003e 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 \u003ci\u003eJournal of Statistical Software \u003c\/i\u003eand \u003ci\u003eThe R Journal\u003c\/i\u003e. His book \u003ci\u003eStatistical Regression and Classification: From Linear Models to Machine Learning\u003c\/i\u003e was the recipient of the Ziegel Award for the best book reviewed in \u003ci\u003eTechnometrics\u003c\/i\u003e in 2017. He is a recipient of his university's Distinguished Teaching Award.\u003c\/p\u003e\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 412\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.9 x 9.1 x 6.1 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e June 20, 2019\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":42738364088383,"sku":"9781138393295","price":145.78,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0105\/8226\/1823\/files\/17c9a90e1ca8f323b1f212459610ad4a.webp?v=1765153058","url":"https:\/\/dhl-adrianne.myshopify.com\/products\/probability-and-statistics-for-data-science-math-r-data-paperback","provider":"BBB","version":"1.0","type":"link"}