Rebecca M. Warner's Applied 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.
It's hard to grasp that you don't have to get the math. This book gives you the essentials to understand your research into categories which brings forth a systemic structure of structures. Structures are of prearranged equations that require specific bits of information to be aligned for acknowledgement of the proper equation to provide the data sets with proper value. This provides the worth of a true or false theory regarded findings from research where in this book shows how to design research configuration.
It's a new language in itself. Speaking in secret code with others in that same socio-linguistic mode, would understand.
Thick and dense, it explains concepts in details. However, the information is so dense that it is easy for readers to get lost. Reading the book by starting from the summary really helps.