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Linear Models with R (Hardcover, 2nd edition)
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Linear Models with R (Hardcover, 2nd edition)
Series: Chapman & Hall/CRC Texts in Statistical Science
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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. The book incorporates
several improvements that reflect how the world of R has greatly
expanded since the publication of the first edition. New to the
Second Edition Reorganized material on interpreting linear models,
which distinguishes the main applications of prediction and
explanation and introduces elementary notions of causality
Additional topics, including QR decomposition, splines, additive
models, Lasso, multiple imputation, and false discovery rates
Extensive use of the ggplot2 graphics package in addition to base
graphics 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.
General
Imprint: |
Chapman & Hall/CRC
|
Country of origin: |
United States |
Series: |
Chapman & Hall/CRC Texts in Statistical Science |
Release date: |
July 2014 |
First published: |
2014 |
Authors: |
Julian J. Faraway
|
Dimensions: |
240 x 158 x 18mm (L x W x T) |
Format: |
Hardcover - Unsewn / adhesive bound
|
Pages: |
274 |
Edition: |
2nd edition |
ISBN-13: |
978-1-4398-8733-2 |
Categories: |
Books >
Science & Mathematics >
Mathematics >
Probability & statistics
Promotions
|
LSN: |
1-4398-8733-0 |
Barcode: |
9781439887332 |
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