Description
Multi- and Megavariate Data Analysis (3rd Ed. revised)
Basic Principles and Applications
Author: ERIKSSON L.
Language:Subjects for Multi- and Megavariate Data Analysis (3rd Ed. revised):
Approximative price 138.35 €
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Publication date: 04-2013
491 p. · Hardback
491 p. · Hardback
Description
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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.
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