Diplomovou práci věnuji problematice statistických metod a jejich využití při hodnocení uchazečů o zaměstnání. Konkrétně se bude jednat o aplikaci faktorové analýzy a jednofaktorové analýzy rozptylu. Diplomovou práci rozdělím na 4 části. První tři části zasvětím pouze faktorové analýze, poslední část se bude týkat výhradně analýzy rozptylu. V první části se zaměřím na průzkumovou analýzu dat, s cílem ověřit předpoklady faktorové analýzy. Nejdříve vyhledám vybočující a extrémní hodnoty jednotlivých proměnných. Následovat bude výpočet základních charakteristik proměnných, testování heteroskedasticity a vysvětlení smyslu každé z proměnných. Hlavní důraz bude kladen na testování normality jednotlivých proměnných, a to jak pomocí statistických testů, tak s využitím grafických nástrojů. Druhá část bude věnována matematickému modelu faktorové analýzy. Ve třetí části se zaměřím na samotné provedení faktorové analýzy. Jako první budu testovat předpoklady vztahující se na korelační matici. Následovat bude kompletní provedení faktorové analýzy v SPSS popř. NCSS. Nejdříve použiji metodu faktorové rotace Varimax. Pro odhady parametrů faktorového modelu použiji metodu hlavních komponent (pro výchozí řešení) a metodu hlavních os. Pro srovnání faktorové rotace Varimax provedu rovněž ortogonální faktorovou rotaci Quartimax při metodě hlavních os. Ve čtvrté části se zaměřím na jednofaktorovou analýzu rozptylu, vzhledem k tomu, že mám k dispozici proměnné věk a národnost, které jsem nevyužila ve faktorové analýze. Nejdříve opět provedu průzkumovou analýzu dat, popíšu jednofaktorový model analýzy rozptylu a posléze analýzu provedu v SPSS popř. NCSS. Pokud prokážu vliv alespoň jednoho z faktorů, budu pokračovat v hlubší analýze mnohonásobného porovnávání.

Determination of the stock expected return is an important element of asset management. This paper presents an Arbitrage Pricing Theory model, which strives to estimate the expected return explaining the historical volatility of the stock prices. This paper presents the model as it was introduced, necessary extension for application to a small market included. Statistical methods on which the model has been build are discussed -- factor analysis completed by principal component analysis. In the practical part, the model is applied to the Czech market with an assessment of the success of the application. The forces which were expected to represent risk factors for the market have been examined as well. It will be shown that the model may contribute to the understanding of risk behaviour of the stocks.

The thesis deals with pre-processing of two data sets with information on clients, loans and debit cards. The data sets were separately pre-processed and modeled by SPSS Modeler using a number of methods and algorithms. For the modeling purposes, three classification data mining tasks were defined: loan approving or rejecting, loan rating and debit card type assignment. By using the selected methods of machine learning techniques the classification models were built for each task. Models accuracy was tested by script written in SPSS language for automation. All tasks were supplemented by clustering technique based on latent factors gained by factor analysis. Factor analysis combined with clustering presents another approach in pattern discovery.

Title: About identification of motor predispositions in triathlon Aims: The aim of our study was to find and verify appropriate indicators predicting the on-coming performance in a short triathlon and determine their level for the junior category. Methods: In our study, we combined quantitative and qualitative approaches with a predominance of quantitative methods. In the first phase of the research, we used quantitative methods, confirmatory factor analysis for verification of models of predispositions and elaboration of performance standards for individual tests by means of T-points. In the second part of the research, we used the qualitative method (casuistic studies) to validate the test battery and its application in practice. Results: We have compiled a structural model of motor predispositions for short triathlon, which explained 91% of all cross-correlations of seventeen used indicators. Predispositions for triathlon were categorized into five separate groups; for swimming, cycling and running (i.e. according to individual disciplines), and functional and psychological predispositions. Finding a lower limit boundary of performance in the completed tests is considered to be the most important issue for the assessment of future performance in triathlon. As a lower limit we have set the zone...

The aim of this thesis is the identification of main factors that determines the structure and character of international trade with goods among China and se-lected countries of the European Union which are Czech republic, Kingdom of the Netherlands and Kingdom of Sweden. The introductory part describes various rea-sons that make countries participate in international trade and describes factors that influence the trade. Subsequently, the paper is focused on analysis of com-modity structure of trade of the mentioned countries and factor intensity analysis. Based on the results of these analysis the main factors that determine the bilateral flow of goods between China and each one of the selected countries, are identified. As a result of this paper we can conclude that the main factors that determine the trade are comparative advantages of the countries. We can distinguish between qualitative comparative advantage that is typical for countries of the European union or cost-based comparative advantage typical for China.

Bayesian factor analysis - abstract Factor analysis is a method which enables high-dimensional random vector of measurements to be approximated by linear combinations of much lower number of hidden factors. Classical estimation procedure of this model lies on the cho- ice of the number of factors, the decomposition of variance matrix while keeping identification conditions satisfied and on the appropriate choice of rotation for better interpretation of the model. This model will be transferred into bayesian framework which offers the usage of prior information unlike the classical appro- ach. The number of hidden factors can be considered as a random parameter and the dependency of each measurement on at most one factor can be forced by suitable specification of prior distribution. Estimates of model parameters are based on posterior distribution which is approximated by Monte Carlo Markov Chain methods. Bayesian approach solves the problem of selection of the num- ber of factors, the model estimation and the ensuring of the identifiability and the interpretability at the same time. The ability to estimate the real number of hidden factors is tested in a simulation study. 1

This work discusses the detection of latent variables, which create indices of economic freedom. Firstly, we present the most well-known indices of economic freedom (IEF, EFW). Secondly, this work discusses multivariate statistical method - factor analysis, which we use to detect latent variables. We show different methods of estimates in factor analysis and we focus on principal factor method. Furthermore, we compare already defined methods by analysing the structure of EFW index. According to estimated models, we interpret detected latent variables. We use statistical software SPSS and R for factor analysis of EFW index.

My diploma thesis focuses on the comparison of possibilities of the statistical software SAS and SPSS in the area of the factor and cluster analysis and the multidimensional scaling. They deal with the methods for identifying groups of the similar statistical values (variables). The ascertained relations among the variables can serve to decrease the proportion vectors of the variables, which describe the individual monitored objects (statistical units), which helps us to apply other various methods, for example the regression or discriminant analysis. By one of the ways for finding the similarity of variables in the cluster analysis or the multidimensional scaling is searching for their relations. Whereas the base of the factor analysis is the formulation of the relation between two variables by means of the covariances, eventually Pearson correlation coefficient, it is possible to use also coefficients of correlation for the cluster analysis and the multidimensional scaling, in some case other measures. The thesis describes mainly the command syntax of the procedures implemented in SAS and SPSS. The meaning of the individual parametres and the partial specifications of each command are explained. The results gained by various types of analyses are compared on the basis of the real dataset. The possibilities of the statistical software SAS and SPSS are evaluated in the conclusion and it is referred to their advantages or disadvantages. The attention is also paid, for example, to the form of the input dataset, to the quaility of outputs or to the partial methods.

This thesis is focused on analysis of the factors that influence the yields of the wheat. This thesis is divided into three parts. The first part opens the problem of wheat cultivation. The second one concerns the methodologies of creating the econometrics models and the third one solves the problem as a whole. Considering a large data file I have a need to reduce it by the factor analysis. I estimate relevant econometric model by application different econometrics methods. This model will show the influences of technological, soil and climatic factors on the yields of wheat. At the end I confront the observed variables with predicted ones by the graininess of soil, climate and the year of the crops.

Title: Service Quality evaluation in fitness club Fit EffectFitness  Wellness Objectives: The main goal of this thesis is to do a marketing research of service quality in fitness club Fit EffectFitness  Wellness. The research is conducted using a questionnaire survey based on Brady's model. Another objective is to verify the reliability of individual questions in the questionnaire based on the results of statistical method of factor analysis. Methods: The primary method selected for this research was questionnaire with structure based on Brady's model. Another method of direct observation was applied in the environment of fitness club Fit EffectFitness Wellness. In addition, the structured interview with open questions was held at the fitness club to obtain basic background information. The statistical method of factor analysis was used to ensure the reliability of each individual question in the questionnaire. Results: The research results are represented in graphs, tables and classification crosses. Suggestions and recommendations were made for fitness club Fit EffectFitness  Wellness according to the obtained results. Keywors: sport services, customer, quality, satisfaction, factor analysis