Exploratory Data Analysis Using R: Chapman & Hall/CRC Data Mining and Knowledge Discovery

I Analyzing Data Interactively with R  1. Data, Exploratory Analysis, and R  2. Graphics in R  3. Exploratory Data Analysis: A First Look  4. Working with External Data  5. Linear Regression Models  6. Crafting Data Stories  II Developing R Programs  7. Programming in R  8. Working with Text Data  9. Exploratory Data Analysis: A Second Look  10. More General Predictive Models  11. Keeping It All Together

Ronald K. Pearson currently works for GeoVera, a property insurance company in Fairfield, California, primarily in the analysis of text data. He holds a PhD in Electrical Engineering and Computer Science from the Massachussetts Institute of Technology and has published conference and journal papers on topics ranging from nonlinear dynamic model structure selection to the problems of disguised missing data in predictive modeling. Dr. Pearson has authored or co-authored books including Exploring Data in Engineering, the Sciences, and Medicine (Oxford University Press, 2011) and Nonlinear Digital Filtering with Python, co-authored with Moncef Gabbouj (CRC Press, 2015). He is also the developer of the DataCamp course on base R graphics.