This diploma aims to analyze the development of the European Union Member States for last thirty years in terms of demographic indicators. First chapter is focused on the historical development of the world's population, followed by the development of the European population and political history of the European Union. Next chapter is focused on the most commonly used demographic indicators for international comparisons divided into groups according to demographic processes, their interpretation and calculation. The main part of the work is analysis of selected indicators for the Member States of the EU with regard to the European average of 27 Member States in the period between 1981 and 2011. Another chapter is devoted to modify data for above mentioned simple analysis and cluster analysis, which is located in the last chapter. Cluster analysis was performed using Euclidean distance and using nearest and furthest neighbor and Ward's method. In 1981 the furthest neighbor method divided Member States into five clusters and in 2011 the Ward's method divided Member States again within five clusters, but with a different composition. Original data for Multidimensional description is added to annex with the results of calculations and graphs.

The aim of this thesis is to examine the cluster analysis ability segment the data set by selected methods. The data sets are consisting of quantitative variables. The basic criterion for the data sets is that the number of classes has to be known and the next criterion is that the membership of all object to each class has to be known too. Execution of the cluster analysis was based on knowledge about the number of classes. Classified objects to individual clusters were compared with its original classes. The output was the relative success of classification by selected methods. Cluster analysis methods are not able to determine an optimal number of clusters. Estimates of the optimal number of clusters were the second step in analysis for each data set. The ability of selected criteria identify the original number of classes was analyzed by comparing numbers of original classes and numbers of optimal clusters. The main contribution of this thesis is the validation of the ability of selected cluster analysis methods to identify similar objects and verify the ability of selected criteria to estimate the number of clusters corresponding to the real file distribution. Moreover, this work provides a structured overview of the basic cluster analysis methods and indicators for estimating the optimal number of clusters.

The main objective of the thesis is to describe situation on the current computer games market in Czech Republic and with use of own market research to reveal behavior, usage and preferences of consumers on this market. Based on this data significant market segments should be revealed and appropriate conclusions and recommendations useful for marketing communication should be given for them. Own market research is of quantitative character and is realized in form of Internet questionnaire. Data obtained from this questionnaire are analyzed with help of pivot tables in MS Excel. IBM SPSS Statistics 20 is used for uncovering market segments and expansion of their profiles. The output of the thesis is detection of 5 major market segments and formulation of basic recommendations on marketing mix level for each market segment.

The aim of this work is a statistical analysis of expenditures of households on culture, description of current economical situation in the field of cinematography, characteristics of a cinemagoer and a projection of future developmental tendencies of cinemas. The first two chapters are dedicated to a description of the current state of the Czech cinematography and information about the evolution of the Czech film production. The third theoretical part describes basic statistical methods used in the practical part of this work. The fourth part is focused on a film viewer -cinemagoer using MML-TGI method and it also includes analysis of the dependence of expenditures of households for culture on the cinema ticket price. The fifth part is dedicated to a projection of the future development of the attendance and receipts of cinemas. The final chapter deals with the state of European cinematography.

Tato práce se zabývá technologiemi velkých dat v kontextu měření parametrů sítě. Popisuje téma velkých dat a jejich využití, představuje základní parametry sítě, jejich měření a metody zhodnocení. Vyhodnocuje RTR NetTest aplikaci, testovací proceduru a měřené parametry. Byla vytvořena skupina nástrojů pro posouzení základních kvantitativních parametrů mobilní sítě na základě dat z databáze RTR. Rozbor denního efektu shrnuje časovou proměnlivost sítě. Chování v prostoru je posouzeno binováním a shlukovou analýzou, současně se srovnáním řízeného testování a crowdsourcingu.

The aim of this study is evaluation of using multi-dimensional statistical analyses methods as a tool for simulations of reliability of distribution network. Prefered methods are a cluster analysis (CLU) and a principal component analysis (PCA). CLU is used for a division of objects on the basis of their signs and a calculation of the distance between objects into groups whose characteristics should be similar. The readout can reveal a secret structure in data. PCA is used for a location of a structure in signs of multi-dimensional matrix data. Signs present separate quantities describing the given object. PCA uses a dissolution of a primary matrix data to structural and noise matrix data. It concerns the transformation of primary matrix data into new grid system of principal components. New conversion data are called a score. Principal components generating orthogonal system of new position. Distribution network from the aspect of reliability can be characterized by a number of new statistical quantities. Reliability indicators might be: interruption numbers, interruption time. Integral reliability indicators might be: system average interruption frequency index (SAIFI) and system average interruption duration index (SAIDI). In conclusion, there is a comparison of performed SAIFI simulation according to negatively binomial division and provided values from a distribution company. It is performed a test at description of sign dependences and outlet divisions.

This work deals with the classification of cardiac cycles, which uses a method of dynamic time warping and cluster analysis. Method of dynamic time warping is among the elderly, but for its simplicity compared to others is still very much used, and also achieved good results in practice. Cluster analysis is used in many fields such as marketing or just for biological signals. The aim of this work is a general introduction to the ECG signal and the method and implementation of dynamic time warping algorithm. Subsequently, cluster analysis and finally the creation of the user interface for the algorithms.

Master´s thesis is focused on cluster analysis. Clustering has its roots in many areas, including data mining, statistics, biology and machine learning. The aim of this thesis is to elaborate a recherche of cluster analysis methods, methods for determining number of clusters and a short survey of feature selection methods for unsupervised learning. The very important part of this thesis is software realization for comparing different cluster analysis methods focused on finding optimal number of clusters and sorting data points into correct classes. The program also consists of feature selection HFS method implementation. Experimental methods validation was processed in Matlab environment. The end of master´s thesis compares success of clustering methods using data with known output classes and assesses contribution of feature selection HFS method for unsupervised learning for quality of cluster analysis.

The thesis deals with selected classification methods. The thesis describes the basis of cluster analysis, discriminant analysis and theory of classification trees. The usage is demonstrated by classification of simulated data, the calculation is made in the program STATISTICA. In practical part of the thesis there is the comparison of the methods for classification of real data files of various extent. Classification methods are used for solving of the real task – prediction of air pollution based of the weather forecast.

Determinants of Regional Differentiation of Mortality in the Czech Republic Abstract There are considerable differences in socioeconomic and sociodemographic factors influencing mortality on the individual and also on the aggregate levels. These differences were observed and explained in many countries of the world. The objective of this thesis is to find and evaluate the most significant external factors which influence actual regional differentiation of mortality in districts of the Czech Republic. The objective was achieved by means of the demographic and statistical analysis methods. First, there was a comparison of mortality rates calculated for each of the socioeconomic clusters. It was found out that higher mortality rates appeared among men and women living in the districts with unfavourable external conditions. Using the Poisson log-linear model, the most important factors influencing differences in mortality rates in districts of the Czech Republic were identified. These factors are: share of the unemployed, share of the divorced, share of university-educated people and the number of physicans in hospitals per 1000 inhabitants. Share of the unemployed seems to be the most significant factor. There is a correlation between this factor and the total mortality rate as well as the leading causes of...