Chapman & Hall/CRC Texts in Statistical Science

Highlight, take notes, and search in the book In this edition, page numbers are just like the physical edition

Bayesian Modeling and Computation in Python (Chapman & Hall/CRC Texts in Statistical Science)

Elements of Simulation (Chapman & Hall/CRC Texts in Statistical

Essentials of Probability Theory for Statisticians (Chapman & Hall

Tree-Based Methods for Statistical Learning in R on Apple Books

Chapman and Hall/CRC Texts in Statistical Science Ser

Statistical Theory: A Concise Introduction (Chapman & Hall/CRC

A Hands-On Way to Learning Data Analysis Part of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with R, Second Edition explains how to use linear models in physical science, engineering, social science, and business applications.

Linear Models with R [Book]

Stochastic Processes with R: An Introduction (Chapman & Hall/CRC

Statistical Testing Strategies in the Health Sciences (Chapman

Introduction to Multivariate Analysis (Chapman & Hall/CRC Texts in

Statistical Rethinking: A Bayesian Course with Examples in R