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Full Description
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.
Contents
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
