Linear Models with R

Name: Linear Models with R
Brand: CRC Press
Price: 83.75 AUD
Availability: PreOrder

By: Julian J. Faraway

Write A Review

eText | 26 March 2025 | Edition Number 3

At a Glance

Format
ePUB

New Edition

Published: 19th April 2016

eText

$83.75

or 4 interest-free payments of $20.94 with

Available: 26th March 2025

Preorder. Online access available after release.

Read online on

Desktop

Tablet

Mobile

Not downloadable to your eReader or an app

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.

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, Third Edition explains how to use linear models in physical science, engineering, social science, and business applications. The book incorporates several improvements that reflect how the world of R has greatly expanded since the publication of the second edition.

New to the Third Edition

40% more content with more explanation and examples throughout
New chapter on sampling featuring simulation-based methods
Model assessment methods discussed
Explanation chapter expanded to include introductory ideas about causation
Model interpretation in the presence of transformation
Crossvalidation for model selection
Chapter on regularization now includes the elastic net
More on multiple comparisons and the use of marginal means
Discussion of design and power

Like its widely praised, best-selling predecessor, this edition combines statistics and R to seamlessly give a coherent exposition of the practice of linear modeling. The text offers up-to-date insight on essential data analysis topics, from estimation, inference, and prediction to missing data, factorial models, and block designs. Numerous examples illustrate how to apply the different methods using R.