Skip to content

Components of Variance (Chapman & Hall/CRC Monographs on Statistics and Applied
Stock Photo: Cover May Be Different

Components of Variance (Chapman & Hall/CRC Monographs on Statistics and Applied Probability) Paperback - 2019

by Cox, D.R

  • Used
  • Good
  • Paperback
Drop Ship Order

Description

paperback. Good. Access codes and supplements are not guaranteed with used items. May be an ex-library book.
Used - Good
NZ$226.52
FREE Shipping to USA Standard delivery: 7 to 14 days
More Shipping Options
Ships from Bonita (California, United States)

Details

About Bonita California, United States

Biblio member since 2020
Seller rating: This seller has earned a 5 of 5 Stars rating from Biblio customers.

Terms of Sale: 30 day return guarantee, with full refund including original shipping costs for up to 30 days after delivery if an item arrives misdescribed or damaged.

Browse books from Bonita

From the publisher

Identifying the sources and measuring the impact of haphazard variations are important in any number of research applications, from clinical trials and genetics to industrial design and psychometric testing. Only in very simple situations can such variations be represented effectively by independent, identically distributed random variables or by random sampling from a hypothetical infinite population.

Components of Variance illuminates the complexities of the subject, setting forth its principles with focus on both the development of models for detailed analyses and the statistical techniques themselves. The authors first consider balanced and unbalanced situations, then move to the treatment of non-normal data, beginning with the Poisson and binomial models and followed by extensions to survival data and more general situations. In the final chapter, they discuss ways of extending and assessing various models, including the study of exceedances, the use of nonlinear representations, the study of transformations of the response variable, and the detailed examination of the distributional form of the underlying random variables.

Careful signposting and numerous examples from genetic data analysis, clinical trial design, longitudinal data analysis, industrial design, and meta-analysis make this book accessible - and valuable - not only to statisticians but to all applied research scientists who use statistical methods.