Summary
Contents
Subject index
Analysis of variance (ANOVA) constitutes the main set of statistical methods used by students and researchers to analyse data from experiments. This expertly written textbook adopts a pioneering approach to ANOVA with an emphasis on confidence intervals rather than tests of significance.
Key features of the book include: extensive coverage; strong emphasis upon practical examples; web-based links to sample questions and answers; student-focused throughout, it offers a comprehensive introduction to ANOVA using confidence intervals. The chapters have been organized to fit onto a typical lecture programme and is well-structured and practical, invaluable for undergraduates and postgraduate students taking courses in quantitative methods across the social sciences.
Complex Factorial Designs
Complex Factorial Designs
A factorial analysis of data from a J × K design can be based on any of the models (cell means, main effects, saturated two-factor ANOVA, or simple effects) discussed in Chapter 4. Multiplicity issues, similar to those discussed in the context of single-factor designs in Chapter 2, arise when factors have multiple levels. If J > 2 and K > 2 (that ...
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