Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) - Image 1

£48.99

CRC Press Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)

Name: Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)
Brand: CRC Press
Price: 45.85 GBP
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Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition presents linear structures for modeling data with an emphasis on how to incorporate specific ideas (hypotheses) about the structure of the data into a linear model for the data. The book carefully analyzes small data sets by using tools that are easily scaled to big data. The tools also apply to small relevant data sets that are extracted from big data. New to the Second Edition Reorganized to focus on unbalanced data Reworked balanced analyses using methods for unbalanced data Introductions to nonparametric and lasso regression Introductions to general additive and generalized additive models Examination of homologous factors Unbalanced split plot analyses Extensions to generalized linear models R, Minitab®, and SAS code on the author’s website The text can be used in a variety of courses, including a yearlong graduate course on regression and ANOVA or a data analysis course for upper-division statistics students and graduate students from other fields. It places a strong emphasis on interpreting the range of computer output encountered when dealing with unbalanced data.

Product Specifications

Brand: CRC Press
Format: paperback
ASIN: 036773740X
Category: Books > Subjects > Business, Finance & Law > Management > Balanced Scorecard
Domain: Amazon UK
Release Date: 18 December 2020
Listed Since: 14 October 2020

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CRC Press Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)

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