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Visualization of Multivariate Statistical Data
 Maroušek, Vít ; Pecáková, Iva (advisor) ; Černý, Jindřich (referee)
The thesis deals with the possibilities of visualization of multivariate statistical data. Since this is a very broad area the thesis is divided into four sections, two of which are theoretically and two practically oriented. The first section is devoted to theoretical aspects of data visualization. It contains information about the building blocks of graphs, and how the brain processes graphs in various stages of perception. The second section charts the available chart types that can be used to display data. Selected types of graphs for continuous and discontinuous multidimensional data are described in detail. The third section focuses on available software tools for creating graphs. The section describes several programs, with focus on STATISTICA, R and MS Excel. The knowledge gained in previous chapters was sufficient source of information to perform a graphical analysis of multidimensional continuous and discrete data and using advanced analytical methods in the last section. This analysis is performed separately on the data file with continuous variables and on a data file with discontinuous (categorical) variables.
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The graphical data analysis in various statistical computing systems
 Maroušek, Vít ; Pecáková, Iva (advisor) ; Černý, Jindřich (referee)
Goal of my thesis is to show and compare various ways of graphical data analysis in statistical computing systems. This area is still developing, new techniques are being discovered and the already known are being developed. This work is split into three parts, one theoretical, one comparing and one general with new ideas. The first part is theoretical and is dedicated to classification of statistical variables. For statistical computing systems I offer a simplified classification because of the way they treat some types of variables. Second part of my work compares graphical outputs of three most used statistical computing systems SAS, SPSS and STATISTICA. This comparison is based on some of the most commonly used graphical methods. The outputs are tables with detailed description and examples of graphs from each system are attached. The last part is focused on the general graphical data exploration and follows the simplified classification of variables. In this part I use common graphical techniques and introduce some new or fewer used techniques. Many of them haven't been described in any Czech literature yet. Almost all the graphs presented in this work were created by me in various statistical computing systems. Two were copied from literature because of serious problems with the process of their creation.
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1 Maroušek, V.
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