Statistical Data Cleaning with Applications in R

The production of clean data is a complex process that requires both technical know-how and statistical expertise. Statistical Data Cleaning with Applications in R equips the reader with the tools to rise to this challenge with a clear reference to good practice that combines knowledge from the fields of statistics and software engineering with the common theme of data cleaning for statistical purposes. Many examples are presented in the popular R language, but are not aimed to be R-specific. Users of this book will be able to design data cleaning processes for either one-off analytical purposes or for setting up production systems that clean data on a regular basis.

 With constant reference to the statistical value chain, the authors address the preparation of technically processable data, data validation and statistical techniques for solving issues such as incompleteness, contradictions and outliers; and data cleaning strategy, integration of data cleaning components and quality monitoring.