The aim of the thesis is to classify european countries in terms of their business climate using the method of cluster analysis over the years 2008-2013. Changes in classification during this period are associated with events of global significance (e.g. World financial crisis) or local importance (reforms, EU strategy...). Data base consists of indicators describing administrative, financial and law environment for doing business and are publicated by World Bank. Clusters indicate both geographic conditionality and specific attributes of these clusters, which suggest countries with better/worse conditions in some of the areas. Particular attention is given to development in the Czech republic. There was significant change in classificiation between 2008 and 2009 and subsequently became stable. The results of analysis correspond to the existing rankings and indicators of business demography. Potentials for improvement which might leed to stabel economic development according to the conducted analysis are outlined in the end of the thesis (f.e. implementation of unified administrative points, electronization and further simplification of bureaucratic processes).

Master thesis deals with dividing destricts of the Czech Republic in to clusters acording to demographic indicators during the year 2011. After the theoretical introduction with exploratory data analyiss, factor analysis and cluster analysis is described practical implementation of agglomerative hierarchical clustering. Within the frame cluster analysis we compare results calculated by four methods of clustering, which are the single linkage method, the complete linkage method, the average linkage method and Ward's method. At the conclusion we select the method which divides destricts of the Czech Republic in to the clusters the best. Master thesis includes a prezentations of discovere results with the help of dendrograms and cartograms. The analysis were carried out with the help of the statistical program STATISTICA.

The principal goal of the master thesis is to explore the similarities and possible differences among customers of infant milks. Based on those findings, the customers are clustered into various segments, which are extremely homogenous within each one, but significantly heterogeneous outside each of them. The second goal of the thesis is to suggest the best marketing solutions for each revealed segment. The work is divided into two parts, theoretical and practical. The theoretical part describes the process of market segmentation. The characteristics of the infant milk market and the description of infant milk types are described in the practical part. The customers' segmentation is designed according to primary and secondary research. Secondary data is based on data from project MML-TGI and content analysis. The data from my own primary research are processed by IBM SPSS statistics version 20. Among the main finding of the thesis was defining 5 segments of the infant milk customers. The work characterizes all of them and special term is chosen for each of the segment. Finally, the relevant marketing solutions are suggested for each of the segment.

The master thesis deals with the problem of european energy security. The thesis covers also the cluster analysis, which assesses the current state of security in the individual member states. At the same time, the very last part of the thesis proposes measures to strengthen the EU's energy independence.

Nowadays taxes are the most important tax income of the state budget and at the same time they affect the standard of living of the population in various ways. Although the countries try to harmonize tax systems, there are still considerable differences between them. The aim of the thesis is to capture taxes in the Czech Republic from the point of view of statistics and then perform the comparison within the countries of the European Union. The thesis contains a brief characterization of the national accounts and the classification of the taxes in the national accounts according to the ESA 2010. It further deals with the description of the Czech tax system, including a definition of the individual taxes. The subsequent section captures the tax burden expressed by tax quota and the rest of the thesis is devoted to the cluster analysis, which is then applied to the data from the annual national accounts. Using cluster analysis, EU countries have been divided into groups according to similarities and differences in tax systems and in particular on the basis of the tax quota.

Cluster analysis is a popular method of multivariate statistics. Based on mutual similarities between objects this method is able to classify and divide objects into several groups or clusters. The results of the clustering can be different by using different methods, measures of distance and procedures. The main aim of this thesis is to compare the results of several methods of cluster analysis with the known classification of classes from the original data file. In total, there are 15 data files, which were analyzed and each of them contained known information about the right allocation of objects in groups. The success of clustering of each method was calculated by comparing the known classification of classes and resulted clusters. In addition to the comparison of individual methods of cluster analysis was compared the impact of standardization and correlation to the success of each method. To reflect the distance betweeen the objects within each clusters, squared Euclidean distance was used. The results of this thesis point out that better success of clustering were achieved in the case of correlated variables in data file. The succes of clustering was higher about 2 percent points than in the case when correlated variables were deleted from data set. The methods divided 69,8 % objects before standardization and 70,8 % objects after standardization. The results also show a large importance of standardization in the case of Ward´s method. After standardization this method rank the most objects into correct classification classes and were more succesful, about nine percent points. In the case of correlated variables is the succes of the method 76,4 %. Standardization positively influences also centroid method and the method of farthest neighbour. Median method, nearest neighbour method and the method of average linkage achieve higher success of clustering in the case of original, nonstandardized variables (uneven variables).

Objective of this thesis is cluster analysis of political parties and individual politicians in Chamber of Deputies of the Parliament of the Czech Republic. In theoretical part, legislative process in Czech Republic is explained and political situation in Chamber of Deputies is described. Also cluster analysis theory is explained. In practical part, firstly, cluster analysis of political parties was performed, than of individual members of parliament. The furthest neighbor and Ward's methods were used in this part. On the basis of discovered facts, it's possible to confirm compactness of coalition and also of conservative opposition. In specific political parties, as most united behave TOP 09 members and least ČSSD members of parliament.

This Masters Thesis is focused on detergent market in the Czech Republic and its market segmentation. The goal of this thesis is to find differences and similarities between consumers and to uncover the segments which are internally homogeneous and externally heterogeneous, and to suggest a marketing approach for each segment. Theoretical part of this thesis is about theoretical explanation of the market segmentation process, different approaches to segmentation and methods of segmentation. There is also a description of the detergent market in the Czech Republic. The analytical part is focused on segmentation process itself. The segmentation is based on both primary and secondary data. The revealed segments are then described in detail. There is a suggested marketing approach how to effectively address each segment.

The goal of the master's thesis is to find out similarities or differences among consumers in the Czech beer market by using primary and secondary research and content analysis. The thesis contains two parts, the theoretical and the practical one. Market segmentation, marketing research and Czech beer market are described in the theoretical part. The practical part includes market segmentation by using secondary data (agency data MML-TGI with Data Analyzer software), primary data (own research with SPSS software) and content analysis of print advertisements. Segmentation is realized by variety of methods, e. g. cluster and factor analysis, general analysis, contingency tables, MCART analysis, media neutral quintiles etc. Post hoc segmentation (forward and backward) is used in this thesis. At the end of this master's thesis detected segments are characterized and marketing suggestions for each of them are stated.

This Master's Thesis is focused on analysis of segmentation of the coffee market in the Czech Republic based on similarities and differences between users of coffee. Uncovering segments and development was carried out in a software program Data Analyzer and PASW using data from primary research and unique agency research MML-TGI of company Median s.r.o. The theoretical part presented problems, approaches, method of segmentation and types of coffee. The practical part starts with analyzing and defining the market in the Czech Republic. The target group of users was subsequently characterized by a general analysis. Variables were reduced to the factors by using factor analysis. Then users were put into clusters based on cluster analysis. Segments were characterized in detail using cross-analyzes and multivariate statistical methods. Content analysis expands a current picture of the segments on which other companies target. Finally, there were elaborated appropriate marketing recommendations for the individual segments to their effective positioning.