Model to Meaning: How to Interpret Statistical Models with R and Python

Proposes a consistent workflow that can be applied to (almost) any statistical or machine learning model. Readers will learn how to transform complex parameter estimates into quantities that are readily interpretable, intuitive, and understandable.

Vincent Arel-Bundock is Professor at the Université de Montréal, where he teaches political economy and research methods. His research focuses on making the interpretation of statistical models more rigorous and accessible. Vincent is the creator of the widely-used marginaleffects software package, available for both R and Python.