Springer Texts in Statistics Applied Multivariate Data Analysis

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Bol A Second Course in Statistics The past decade has seen a tremendous increase in the use of statistical data analysis and in the availability of both computers and statistical software. This books presents an easy to read and wide-ranging introduction to techniques in multivariate analysis. It covers all the traditional topics of multivariate analysis including multidimensional contingency tables, logistic regression, cluster analysis, multidimensional scaling, and correspondence analysis. It is the companion volume to Volume I: Regression and Experimental Design published in 1991. The emphasis on the practicalities of the subject, and the author has included numerous analyses of real data sets drawn from a wide range of business, social sciences, and biological sciences settings. There are also many exercises which are designed to extend the analyses of the data sets including the use of statistical computing packages, and to cover further theoretical results relevant to the book. As a result, any student whose work uses these techniques will find this to be an excellent introduction to the subject.

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A Second Course in Statistics The past decade has seen a tremendous increase in the use of statistical data analysis and in the availability of both computers and statistical software. This books presents an easy to read and wide-ranging introduction to techniques in multivariate analysis. It covers all the traditional topics of multivariate analysis including multidimensional contingency tables, logistic regression, cluster analysis, multidimensional scaling, and correspondence analysis. It is the companion volume to Volume I: Regression and Experimental Design published in 1991. The emphasis on the practicalities of the subject, and the author has included numerous analyses of real data sets drawn from a wide range of business, social sciences, and biological sciences settings. There are also many exercises which are designed to extend the analyses of the data sets including the use of statistical computing packages, and to cover further theoretical results relevant to the book. As a result, any student whose work uses these techniques will find this to be an excellent introduction to the subject.


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