{"product_id":"an-introduction-to-data-science-paperback","title":"An Introduction to Data Science - 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\u003eJeffrey S. Saltz\u003c\/b\u003e (Author), \u003cb\u003eJeffrey Morgan Stanton\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eAn Introduction to Data Science\u003c\/strong\u003e is an easy-to-read, gentle introduction for advanced undergraduate, certificate, and graduate students coming from a wide range of backgrounds into the world of data science. After introducing the basic concepts of data science, the book builds on these foundations to explain data science techniques using the R programming language and RStudio\u003csup\u003e(R)\u003c\/sup\u003e from the ground up. Short chapters allow instructors to group concepts together for a semester course and provide students with manageable amounts of information for each concept. By taking students systematically through the R programming environment, the book takes the fear out of data science and familiarizes students with the environment so they can be successful when performing advanced functions. \u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003eThe authors cover statistics from a conceptual standpoint, focusing on how to use and interpret statistics, rather than the math behind the statistics. This text then demonstrates how to use data effectively and efficiently to construct models, predict outcomes, visualize data, and make decisions. Accompanying digital resources provide code and datasets for instructors and learners to perform a wide range of data science tasks. \u003c\/p\u003e \u003cbr\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eJeffrey S. Saltz\u003c\/b\u003e is an Associate Professor at Syracuse University in the School of Information Studies and Director of the school′s Master′s of Science program in Applied Data Science. His research and teaching focus on helping organizations leverage information technology and data for competitive advantage. Specifically, his current research focuses on the socio-technical aspects of data science projects, such as how to coordinate and manage data science teams. In order to stay connected to the \"real world\", Dr. Saltz consults with clients ranging from professional football teams to Fortune 500 organizations. Prior to becoming a professor, Dr. Saltz′s two decades of industry experience focused on leveraging emerging technologies and data analytics to deliver innovative business solutions. In his last corporate role, at JPMorgan Chase, he reported to the firm′s Chief Information Officer and drove technology innovation across the organization. Jeff also held several other key technology management positions at the company, including CTO and Chief Information Architect. He also served as Chief Technology Officer and Principal Investor at Goldman Sachs, where he helped incubate technology start-ups. He started his career as a programmer, project leader and consulting engineer with Digital Equipment Corp. Dr. Saltz holds a B.S. degree in computer science from Cornell University, an M.B.A. from The Wharton School at the University of Pennsylvania, and a PhD in Information Systems from the New Jersey Institute of Technology.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eJeffrey M. Stanton, Ph.D.\u003c\/b\u003e is a Professor at Syracuse University in the School of Information Studies. Dr. Stanton's research focuses on the impacts of machine learning on organizations and individuals. He is the author of \u003ci\u003eReasoning with Data\u003c\/i\u003e (2017), an introductory statistics textbook. Stanton has also published many scholarly articles in peer-reviewed behavioral science journals, such as the \u003ci\u003eJournal of Applied Psychology\u003c\/i\u003e, \u003ci\u003ePersonnel Psychology\u003c\/i\u003e, and \u003ci\u003eHuman Performance\u003c\/i\u003e. His articles also appear in \u003ci\u003eJournal of Computational Science Education\u003c\/i\u003e, \u003ci\u003eComputers and Security\u003c\/i\u003e, \u003ci\u003eCommunications of the ACM\u003c\/i\u003e, \u003ci\u003eComputers in Human Behavior\u003c\/i\u003e, the \u003ci\u003eInternational Journal of Human-Computer Interaction\u003c\/i\u003e, \u003ci\u003eInformation Technology and People\u003c\/i\u003e, the \u003ci\u003eJournal of Information Systems Education\u003c\/i\u003e, the \u003ci\u003eJournal of Digital Information\u003c\/i\u003e, \u003ci\u003eSurveillance and Society\u003c\/i\u003e, \u003ci\u003eand Behaviour \u0026amp; Information Technology\u003c\/i\u003e. He also has published numerous book chapters on data science, privacy, research methods, and program evaluation. Dr. Stanton′s research has been supported through 19 grants and supplements including the National Science Foundation's CAREER award. Before getting his PhD, Stanton was a software developer who worked at startup companies in the publishing and professional audio industries. He holds a bachelor′s degree in Computer Science from Dartmouth College, and a master′s and Ph.D. in Psychology from the University of Connecticut.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 288\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.5 x 9.1 x 7.3 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e October 06, 2017\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":45968818438279,"sku":"9781506377537","price":189.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0601\/2623\/2711\/files\/Yr0gO5Ytn99781506377537.webp?v=1790675469","url":"https:\/\/booksby.splitshops.com\/products\/an-introduction-to-data-science-paperback","provider":"Books by splitShops","version":"1.0","type":"link"}