ABSTRACT
This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book introduces some of the methods available in R for analyzing text data. It devotes to a detailed discussion of some of the ways we can move data into and out of mass storage. The book also introduces the basic notions of exploratory data analysis (EDA), focusing on specific techniques and their implementation in R. It provides an introduction to the issues that arise in analyzing text data and some of the techniques developed to address them. The book also provides the idea of using random variables and probability distributions to model undertainty in data, along with some standard random variable characterizations like the mean and standard deviation. It concludes with five programming examples, worked out in detail, based on the recognition that many of us learn much by studying and modifying code examples that are known to work.
