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Data Science for Business With R
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Data Science for Business With R



February 2021 | 424 pages | SAGE Publications, Inc

Data Science for Business with R, written by Jeffrey S. Saltz and Jeffrey M. Stanton, focuses on the concepts foundational for students starting a business analytics or data science degree program. To keep the book practical and applied, the authors feature a running case using a global airline business’s customer survey dataset to illustrate how to turn data in business decisions, in addition to numerous examples throughout. To aid in usability beyond the classroom, the text features full integration of freely-available R and RStudio software, one of the most popular data science tools available.

Designed for students with little to no experience in related areas like computer science, the book chapters follow a logical order from introduction and installation of R and RStudio, working with data architecture, undertaking data collection, performing data analysis, and transitioning to data archiving and presentation. Each chapter follows a familiar structure, starting with learning objectives and background, following the basic steps of functions alongside simple examples, applying these functions to the case study, and ending with chapter challenge questions, sources, and a list of R functions so students know what to expect in each step of their data science course. Data Science for Business with R provides readers with a straightforward and applied guide to this new and evolving field.

 
Introduction: Data Science, Many Skills
 
Chapter 1: Getting Started with R & RStudio
 
Chapter 2: Rows and Columns
 
Chapter 3: Data Munging
 
Chapter 4: What’s My Function?
 
Chapter 5: Beer, Farms, and Peas and the Use of Statistics
 
Chapter 6: Sample in a Jar
 
Chapter 7: Storage Wars
 
Chapter 8: Pictures vs. Numbers
 
Chapter 9: Map Mashup
 
Chapter 10: Lining Up Our Models
 
Chapter 11: What’s Your Vector, Victor?
 
Chapter 12: Hi Ho, Hi Ho—Data Mining We Go
 
Chapter 13: Word Perfect (Text Mining)
 
Chapter 14: Shiny Web Apps
 
Chapter 15: Time for a Deep Dive

Jeffrey S. Saltz

Jeffrey S. Saltz 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... More About Author

Jeffrey M. Stanton

Jeffrey M. Stanton, Ph.D. 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 Reasoning with Data (2017), an introductory statistics textbook. Stanton has also published many scholarly articles in peer-reviewed behavioral science journals, such as the Journal of Applied Psychology, Personnel Psychology, and Human Performance. His articles also appear in Journal of Computational Science Education, Computers and Security, Communications of the ACM, Computers in Human Behavior, the International... More About Author

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ISBN: 9781544370453
$129.00