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Extraction of information from multidimensional data and its visualization
Vansa, Tibor ; Zvára, Karel (referee) ; Ranocha, Pavel (advisor)
The presented thesis aims to describe and compare methods of extraction of information from high dimensional data, with both continuous and discrete variables. It is focused on principal component analysis, factor analysis, multidimensional scaling and correspondence analysis. The thesis includes generalization of multidimensional scaling and correspondence analysis to case with more random variables. Mutual relations of presented methods are studied. Presented methods are applied on real data and their implementation in statistical softwares R and SPSS is desribed.
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The use of logistic regression in the market research
Brabcová, Hana ; Pecáková, Iva (advisor) ; Ranocha, Pavel (referee)
The aim of this work is to decide the real usage of logistic regression in the market research tasks respecting the needs of final users of research results. The main argument for the final decision is the comparison of its output to the output of an alternative classification method used in practice -- a classification tree method. The topic is divided into three parts. The first part describes the theoretical framework and approaches linked to logistic regression (chapter 2 and 3). The second part analyses the experience with the usage of logistic regression in Czech market research companies (chapter 4) and the topic is closed by applying the method on real data and comparing the output to the classification tree output (chapter 5 and 6).
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