Most of the observable phenomena in the empirical sciences are of a multivariate nature. In financial studies, assets are observed simultaneously and their joint development is analysed to better understand general risk and to track indices. In medicine recorded observations of subjects in different locations are the basis of reliable diagnoses and medication. In quantitative marketing consumer preferences are collected in order to construct models of consumer behavior. The underlying data structure of these and many other quantitative studies of applied sciences is multivariate. Focusing on applications this book presents the tools and concepts of multivariate data analysis in a way that is understandable for non-mathematicians and practitioners who need to analyze statistical data. The book surveys the basic principles of multivariate statistical data analysis and emphasizes both exploratory and inferential statistics. All chapters have exercises that highlight applications in different fields. The third edition of this book on Applied Multivariate Statistical Analysis offers the following new features A new Chapter on Regression Models has been addedAll numerical examples have been redone, updated and made reproducible in MATLAB or R, see www.quantlet.org for a repository of quantlets.
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评分超级好的该主题的入门好基础,数学味道浓厚,例子也足够,用矩阵运算工具开干就成,适合手工把案例和习题都撸一遍。不过可能有人认为太数学化了吧,其实这个是打基础的好办法。
评分超级好的该主题的入门好基础,数学味道浓厚,例子也足够,用矩阵运算工具开干就成,适合手工把案例和习题都撸一遍。不过可能有人认为太数学化了吧,其实这个是打基础的好办法。
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