Data Science in R

Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving (Chapman & Hall/CRC The R Series)

This book presents case studies in statistical computing for data analysis. Each case study addresses a statistical application with a focus on comparing different computational approaches and explaining the reasoning behind them. The case studies can serve as material for instructors teaching courses in statistical computing and applied statistics. The book aids readers in understanding the thought process of data analysis and how to reason about computing.

Table of Contents

Part I: Data Manipulation and Modeling
Chapter 1: Predicting Location via Indoor Positioning Systems
Chapter 2: Modeling Runners’ Times in the Cherry Blossom Race
Chapter 3: Using Statistics to Identify Spam
Chapter 4: Processing Robot and Sensor Log Files: Seeking a Circular Target
Chapter 5: Strategies for Analyzing a 12-Gigabyte Data Set: Airline Flight Delays

Part II: Simulation Studies
Chapter 6: Pairs Trading
Chapter 7: Simulation Study of a Branching Process
Chapter 8: A Self-Organizing Dynamic System with a Phase Transition
Chapter 9: Simulating Blackjack

Part III: Data and Web Technologies
Chapter 10: Baseball: Exploring Data in a Relational Database
Chapter 11: CIA Factbook Mashup
Chapter 12: Exploring Data Science Jobs with Web Scraping and Text Mining