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Drawing on the authors experience in social and environmental research, Correspondence Analysis in Practice, Second Edition shows how the versatile method of correspondence analysis (CA) can be used for data visualization in a wide variety of situations. This completely revised, uptodate edition features a didactic approach with selfcontained chapters, extensive marginal notes, informative figure and table captions, and endofchapter summaries.New to the Second Edition Five new chapters on transition and regression relationships, stacked tables, subset correspondence analysis, analysis of square tables, and canonical correspondence analysis Substantially more figures and tables than the first edition A computational appendix that provides the R commands that correspond to most of the analyses featured throughout the book, making it easy for readers to reproduce the analysesWith 33 years of CA experience, the expert author demonstrates how to use uncomplicated, relatively nonmathematical techniques to translate complex tabular data into more readable graphical forms. CA and its variants multiple CA (MCA) and joint CA (JCA) are suitable for analyses in various fields, including marketing research, the social and environmental sciences, biochemistry, and more.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer,
birth defects, or other reproductive harm.
I was excited to start reading this statistical guide, but my copy arrived with a few pages crumpled. The book itself seems solid for analysis, but the delivery experience could have been better. Hoping to get a replacement soon!
D
Dr. Samira Patel
Great Resource for Statistical Analysis
I bought this second edition of 'Correspondence Analysis in Practice' for a graduate course and it’s been a solid addition to my studies. The examples are clear and the layout is quite intuitive. I appreciate the interdisciplinary approach, making it useful for different fields!
L
Liam Johnson
Useful but a Bit Dense
The content in this book is very informative, but I found some sections to be a bit dense for quick understanding. I was expecting a smoother read based on the title. Still, if you’re into interdisciplinary statistics, it’s worth having around for reference.
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