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Multi- and Megavariate Data Analysis Basic Principles and Applications 2013, by Lennart Eriksson, Tamara Byrne, Erik Johansson, Johan Tryg
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To understand the world around us, as well as ourselves, we need to measure many things, many variables, many properties of the systems and processes we investigate. Hence, data collected in science, technology, and almost everywhere else are multivariate, a data table with multiple variables measured on multiple observations (cases, samples, items, process time points, experiments). This book describes a remarkably simple minimalistic and practical approach to the analysis of data tables (multivariate data). The approach is based on projection methods, which are PCA (principal components analysis), and PLS (projection to latent structures) and the book shows how this works in science and technology for a wide variety of applications. In particular, it is shown how the great information content in well collected multivariate data can be expressed in terms of simple but illuminating plots, facilitating the understanding and interpretation of the data. The projection approach applies to a variety of data-analytical objectives, i.e., (i) summarizing and visualizing a data set, (ii) multivariate classification and discriminant analysis, and (iii) finding quantitative relationships among the variables. This works with any shape of data table, with many or few variables (columns), many or few observations (rows), and complete or incomplete data tables (missing data). In particular, projections handle data matrices with more variables than observations very well, and the data can be noisy and highly collinear. Authors: The five authors are all connected to the Umetrics company (www.umetrics.com) which has developed and sold software for multivariate analysis since 1987, as well as supports customers with training and consultations. Umetrics' customers include most large and medium sized companies in the pharmaceutical, biopharm, chemical, and semiconductor sectors.
- Sales Rank: #1468912 in eBooks
- Published on: 2013-10-10
- Released on: 2013-10-10
- Format: Kindle eBook
Most helpful customer reviews
0 of 0 people found the following review helpful.
Excellent book for a practical understanding of PCA and PLS ...
By Eduardo Solano Granados
Excellent book for a practical understanding of PCA and PLS for multivariate data. It's not for statisticians but for interpretation and analysis of multivariate data processes, which it's my case. Excellent suport for those who take the course of Umetrics and for the SIMCA software but also for other MVDA software for example ProMv, which is the one that I use.
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