A friendly, fun guide to making accurate predictions and revealing relationships in your data using linear and logistic regression.
Regression, a Friendly Guide teaches you to build, assess, and interpret regression models. In each chapter, new modelling paradigms are introduced with simple language and illustrative examples. You’ll steadily build up your theoretical understanding until you can intuitively interpret abstract regression models and their underlying mathematics.
Start off by building linear and logistic regression models with one or more variables, and master regression for count models. Learn to use simulation methods to assess your models, and discover advanced techniques like generalized additive models, penalty methods, and quantile regression. You’ll even learn how to interpret your models and findings for non-technical coworkers, to ensure your whole organization is making reliable decisions driven by accurate analysis.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Matthew Rudd is a mathematician fascinated by statistical modeling, data analysis, and the tensions between theory, practice, and interpretability in data science. He teaches mathematics and statistics at Sewanee (The University of the South), a liberal arts college in Tennessee.