{"product_id":"multivariate-statistics-and-machine-learning-an-introduction-to-applied-data-science-using-r-and-python-paperback","title":"Multivariate Statistics and Machine Learning: An Introduction to Applied Data Science Using R and Python - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eDaniel J. Denis\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eMultivariate Statistics and Machine Learning\u003c\/i\u003e is a hands-on textbook providing an in-depth guide to multivariate statistics and select machine learning topics using R and Python software.\u003c\/p\u003e\u003cp\u003eThe book offers a theoretical orientation to the concepts required to introduce or review statistical and machine learning topics, and in addition to teaching the techniques, instructs readers on how to perform, implement, and interpret code and analyses in R and Python in multivariate, data science, and machine learning domains. For readers wishing for additional theory, numerous references throughout the textbook are provided where deeper and less \"hands on\" works can be pursued.\u003c\/p\u003e\u003cp\u003eWith its unique breadth of topics covering a wide range of modern quantitative techniques, user-friendliness, and quality of expository writing, \u003ci\u003eMultivariate Statistics and Machine Learning\u003c\/i\u003e will serve as a key and unifying introductory textbook for students in the social, natural, statistical, and computational sciences for years to come.\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eDaniel J. Denis, Ph.D., \u003c\/b\u003e is Professor of Quantitative Psychology at the University of Montana, U.S.A, where he has taught applied statistics courses since 2004. He is author of \u003ci\u003eApplied Univariate, Bivariate, and Multivariate Statistics\u003c\/i\u003e and \u003ci\u003eApplied Univariate, Bivariate, and Multivariate Statistics Using Python\u003c\/i\u003e.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 584\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1.23 x 10 x 7 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e December 29, 2025\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":43736585175175,"sku":"9781032454283","price":121.48,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0601\/2623\/2711\/files\/PizusKIre09781032454283.webp?v=1768560628","url":"https:\/\/booksby.splitshops.com\/products\/multivariate-statistics-and-machine-learning-an-introduction-to-applied-data-science-using-r-and-python-paperback","provider":"Books by splitShops","version":"1.0","type":"link"}