Part 4. Advanced methods
In this part of the book, we’ll consider advanced methods of statistical analysis to round out your data analysis toolkit. The methods in this part play a key role in the growing field of data mining and predictive analytics.
Chapter 13 expands on the regression methods in chapter 8 to cover parametric approaches to data that are not normally distributed. The chapter starts with a discussion of the generalized linear model and then focuses on cases where you’re trying to predict an outcome variable that is either categorical (logistic regression) or a count (Poisson regression).
Dealing with a large number of variables can be challenging, due to the complexity inherent in multivariate data. Chapter 14 describes two ...
Get R in Action, Second Edition now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
