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Use of statistical methods in researching socio-economic potential of selected microregion of South Bohemia
HLAVSOVÁ, Veronika
In this work, I looked at the use of statistical methods in researching of socio-economic potential of microregion of Prachatice. I made a several researches, such as detecting the file structure according to various indicators, researching of socio-economic conditions, associations between selected indicators, comparison of views of citizens and council of villages, ascertainment sources of funding of villages and analysis of sustainable life in the villages. Research data was analysed by percent occurrences, kontingent tables and Cluster analysis. I was success at evidence of mutual association between majority of selected characters. I also was concerned with researching contentment with services of villages, opinion on the reasons of economic weakness of villages, token of economic weakness of villages and possibilities for improvement of life in villages. In these researching, I have decided to compare the opinion of citizens and council of villages. In option of citizens and council of villages, I also interested on option for economic weakness of villages. The majority of citizens and council of villages perceive the village in whole or in part as the economically weak. Citizens and council of villages are mostly satisfied with quality of services of villages. Citizens not even council of villages do not perceive causes and tokens of economic weakness of villages as strong causes and tokens, except the low portion of university educated people, who perceive as strong reason of economic weakness of villages council of villages. For the greatest possibility of improving life in villages is strengthen of services and tourism. By examining views of citizens and council of villages for improve life in the villages separately according to view of citizens is greatest possibility strengthen of tourism and according to view of council of villages is greatest possibility strengthen of trading.
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Metody pro stanovení počtu shluků ve statistických programových systémech
Řezanková, H. ; Húsek, Dušan
The paper deals with approaches to determination of the optimal number of groups of objects when objects are clustered by different methods implemented in commercial statistical software packages. These approaches are applied to the example of finding groups of deputies of the Russian parliament on the base of roll-call votes in 2004. The capabilities of software packages S-PLUS, SAS, SPSS, and SYSTAT are compared.
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Informační shlukování kategoriálních dat
Hora, Jan
The EM algorithm has been used repeatedly to identify latent classes in categorical data by estimating finite distribution mixtures of product components. Unfortunately, the underlying mixtures are not uniquely identifiable and, moreover, the estimated mixture parameters are starting-point dependent. For this reason we use the latent class model only to define a set of ``elementary'' classes by estimating a mixture of a large number components. As such a mixture we use also an optimally smoothed kernel estimate. We propose a hierarchical ``bottom up'' cluster analysis based on unifying the elementary latent classes sequentially. The clustering procedure is controlled by minimum information loss criterion.
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Psychosemantic methods: between qualitative and quantitative approaches
Urbánek, Tomáš
Psychosemantic methods can be loosely defined as methods enabling to examine or measure various features of the human psyche in some way, mostly by means of assessing the similarities or differences between meanings, assigned by examinees to the stimuli used in these methods.These methods can be used for illustration of the possible connection between qualitative and quantitative methodologies, since the data obtained this way can be quantitatively analysed and interpreted both on the level of indvidual and /or appropriately selected group of individuals. An example of the psychosemantic method in this article is the Semantic selection test.
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Shluková analýza pro náhodné procesy událostí
Volf, Petr
The paper deals with the statistical analysis of unemployment data. The data are modeled via a discrete-time version of Poisson process. Cluster analysis is employed for selection of sub-populations with similar development of unemployment in recent years. Inside these clusters, an additional analysis of heterogeneity is performed. Numerical example analyzes certain aspects of unemployment development in the Czech Republic in 1993-1998.
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