Rebecca M. Warner's Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked to think about the meaning of equations. Each chapter presents a complete empirical research example to illustrate the application of a specific method. Although SPSS examples are used throughout the book, the conceptual material will be helpful for users of different programs. Each chapter has a glossary and comprehension questions.
Basic Bivariate Techniques Rebecca M. Warner. rankY – .690 double star Sig – two tailed X – blank Y –.007 rankX – blank rankY – .007 N X – 10 Y – 10 rankX – 10 rankY – 10 Spearman's rho X Correlation coefficient X – 1 Y –.859 double ...
This book is a guide to using S environments to perform statistical analyses and provides both an introduction to the use of S and a course in modern statistical methods.
Key features of the book include: interweaving the teaching of statistical concepts with examples from publicly available social and health science data and literature excerpts; thoroughly integrating the teaching of statistical theory with ...
For graduate students in the social and health sciences, featuring essential concepts and equations most often needed in scholarly publications.
Rebecca M. Warner's Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant ...
(See Darroch & Ratcliff, 1972, .) This is usually very much faster than GLM fitting but is less flexible. To use loglin we need to form the frequencies into an array. A simple way to do this is to construct a matrix subscript from the ...
This book is essential reading for anyone who makes extensive use of statistical methods in their work.
This is a text in methods of applied statistics for researchers who design and conduct experiments, perform statistical inference, and write technical reports.
Statistical methods discussed in this book are used to introduce the fundamentals of using R functions and provide ideas for developing further skills in writing R code.
Renowned statistician R.G. Miller set the pace for statistics students with Beyond ANOVA: Basics of Applied Statistics.