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Statistic analysis of marketing data
SYSLOVÁ, Jana
This work analyses marketing data from tourist trade sphere. Statistical units are visitors of South Bohemia from season 2006. There were several points of research such as duration of stay, ways of travel organization, goals for visiting the region or quality assessment of services. Research data was analysed by percent occurrences, contingent tables and Cluster analysis. People who assessed quality of services were divided into four groups by the help of Cluster analysis. In light of utilizable resources were informants divided into five groups. This work investigate also relations between outcomes such as relation between average day costs and ways of residence organization, choosing of accomodation in dependance on travel organization and so on. The most frequent reason for visiting region is getting to know attractive tourist places. Following are tourism, sport, health and relaxation. In light of tourist trade is South Bohemia rated very well. Visitors were the most satisfied with catering services, care of sights and quality of tourist trade employees. Reversely quality of traffic ways should improve markedly. Foreign visitors also feel lack of plain local marking and transparent informations about region.
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Determination of the Optimal Number of Clusters in Statistical Software Systems
Řezanková, H. ; Húsek, Dušan
The paper deals with approaches to determination of the optimal number of groups of objects which are implemented in clustering algorithms in commercial statistical software packages. Some of 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 described.
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Riders
Sviták, David ; Hebák, Petr (advisor) ; Kocúrová, Barbora (referee)
Riders are growing more important as a part of insurance markets. The aim of this thesis is to introduce riders offered by a chosen insurance company in the Czech Republic. The next part is dedicated to the study of a structure of arranged riders in one year. A characteristic of riders and main covers a, which affect the number of arranged riders, are specified by using statistical methods. In the last part, clients are classified based on their owned riders by using cluster analysis. This thesis contains some recommenddations to create new riders.
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Market segmentation and cluster analysis
Zuzák, Jaroslav ; Vilikus, Ondřej (advisor) ; Hebák, Petr (referee)
This bachelor thesis deals with possibilities of statistic-analytical tools in market segmentation (i.e. a marketing concept), which is introduced as well. The theoretical part focuses on cluster analysis and its best-known algorithms, their assumptions and from those following possible usefulness and potential limitations. In the practical part a segmentation study of gallery and museum visitors is conducted on the basis of lifestyle and leasuretime activities variables. The resulting segments are profiled using other variables to create a more real-life image of the visitors and nonvisitors of galleries and museums.
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Classification of electronic documents using cluster analysis
Ševčík, Radim ; Řezanková, Hana (advisor) ; Svátek, Vojtěch (referee)
The current age is characterised by unprecedented information growth, whether it is by amount or complexity. Most of it is available in digital form so we can analyze it using cluster analysis. We have tried to classify the documents from 20 Newsgroups collection in terms of their content only. The aim was to asses available clustering methods in a variety of applications. After the transformation into binary vector representation we performed several experiments and measured the values of entropy, purity and time of execution in application CLUTO. For a small number of clusters the best results offered the direct method (generally hierarchical method), but for more it was the repeated bisection (divisive). Agglomerative method proved not to be suitable. Using simulation we estimated the optimal number of clusters to be 10. For this solution we described in detail features of each cluster using repeated bisection method and i2 criterion function. In the future focus should be set on realisation of binary clustering with advantage of programming languages like Perl or C++. Results of this work might be of interest to web search engine developers and electronic catalogue administrators.
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