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Factors influencing the financial situation of Ph.D. students in the Czech Republic
Zahradníčková, Jana ; Vltavská, Kristýna (advisor) ; Stoklasa, Jan (referee)
Ph.D. students are an integral part of the tertiary education system. Encouragement for doctoral programs and their students is very important because they are the ones who will participate in research projects in the future and they will contribute to society as a whole. The majority of scholarships for Ph.D. students comes from public sources. An important question to be asked is whether the scholarships are sufficient to finance Ph.D. studies and whether there are differences in the amount depending on gender, field of study or region. This thesis aims to answer these questions by applying statistical methods to the results of the survey DOKTORANDI 2014.
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Hodnocení finančního zdraví podniku prostřednictvím logitového modelu
Malá, Tereza
Malá, T. Evaluation of the company's financial health by way of a logistic regression. Diploma thesis. Brno: Mendel University, 2015. The aim of the thesis is on the data obtained from Amadeus database to identify indicators which determine the financial health of a company and then to synthesize a nonlinear model usable for assessing the financial health of the company. The specific method used for modelling such a type of simulation is logistic regression. In this thesis is aim to try to apply mentioned method precisely on financial data and evaluate its usability in context of modelling of the financial health of the economic subjects operating in the Czech market.
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Building a predictive model for bankruptcy
BÜRGER, Pavel
Thesis deals with complex process of creation of new bankruptcy model for predicting business failure, while this process involves selection of quality sample, verification of classification accuracy of already existing bankruptcy models, profile analysis and finally the derivation of specific equation of bankruptcy model. The derivation is performed by using two selected statistical methods, discriminant analysis and logistic regression. Two bankruptcy models Bürger's index DA12 and Bürger's index LR12 were derived by using the mentioned statistical methods. The new models distinct advantage is, unlike already existing and renowned bankruptcy models, that they are focused on classification of micro and small enterprises in terms of Czech Republic, while classification accuracy one year before failure is by individual models 74.8 % and 81.87 %. Derived models have clear interpretation (no grey zone) and easy calculation, which brings a possibility for micro and small entrepreneurs to check their business partners in terms of failure prediction.
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Financial distress prediction of company
MAŇASOVÁ, Helena
The theoretical part of this master thesis deals with creation and solution of financial distress and analysing classification models. In the practical part I defined own methods for financial distress prediction of company using discriminant analysis and logistic regression.
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The Risk of Poverty in the Czech Republic
Klein, Jan ; Bartošová, Jitka (advisor) ; Bína, Vladislav (referee)
The goal of this work is to identify and analyse factors with impact on the income decrease of households under the poverty line. Data used in this work are taken from EU SILC survey. In this work is created a statistical model which help us to discover relevant and irrelevant factors. The situation and it's development is analysed only for Czech households in this work
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The analysis of dependence of the material deprivation of the households in the Czech Republic on the selected indicators
Cafourková, Magdalena ; Řezanková, Hana (advisor) ; Pecáková, Iva (referee)
The aim of this thesis is to analyse the material deprivation of the households with regard to the selected indicators, i.e. the costs that the household spends on housing, a region where the household is located, the number of the members and the dependent children in the household, age and sex of a head of the household, and economic activity and education level of the members of the household. The thesis aims not only to prove the dependence among the selected indicators but also to quantify this dependence by using the odds ratio. The individual effect of all variables was proven except of the one related to the number of the dependent children. It was also demonstrated that the factors constituting a threat for the households by a material deprivation rate vary by the different age groups. However, it can be concluded that across all the age groups, the material deprivation rate is determined by the sex of a head of the household, education level of the members of the household, and the costs that the household spends on housing.
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Using data mining to manage an enterprise.
Prášil, Zdeněk ; Pour, Jan (advisor) ; Novotný, Ota (referee)
The thesis is focused on data mining and its use in management of an enterprise. The thesis is structured into theoretical and practical part. Aim of the theoretical part was to find out: 1/ the most used methods of the data mining, 2/ typical application areas, 3/ typical problems solved in the application areas. Aim of the practical part was: 1/ to demonstrate use of the data mining in small Czech e-shop for understanding of the structure of the sale data, 2/ to demonstrate, how the data mining analysis can help to increase marketing results. In my analyses of the literature data I found decision trees, linear and logistic regression, neural network, segmentation methods and association rules are the most used methods of the data mining analysis. CRM and marketing, financial institutions, insurance and telecommunication companies, retail trade and production are the application areas using the data mining the most. The specific tasks of the data mining focus on relationships between marketing sales and customers to make better business. In the analysis of the e-shop data I revealed the types of goods which are buying together. Based on this fact I proposed that the strategy supporting this type of shopping is crucial for the business success. As a conclusion I proved the data mining is methods appropriate also for the small e-shop and have capacity to improve its marketing strategy.
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Determinants of claim occurrence: case of Motor Third Party Liability insurance
Novotný, Jakub ; Bolcha, Peter (advisor) ; Potužák, Pavel (referee)
In this paper the hypotheses related to individual variables used for segmentation of Motor Third Party Liability (MTPL) insurance by Czech insurance companies are tested. Summary of papers focused on this topic and development of insurance market segmentation in European Union are presented in the first part of this thesis. The first part of this paper is extended by the analysis of actual MTPL segmentation in Czech Republic. The estimation of marginal effects of exogenous variables on probability of occurrence a claim is described in empirical part. For the estimation of parameters I use the logistic regression. Specific models for small and large claims are created. The most significant variables positively correlated with probability of occurrence a claim are engine capacity, young age and region Prague. The most significant variables negatively correlated with probability of occurrence a claim are historical car, old age, number of months without any claim and region South Moravia. My results are compared to the results of other papers.
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Comparison of selected classification methods for multivariate data
Stecenková, Marina ; Řezanková, Hana (advisor) ; Berka, Petr (referee)
The aim of this thesis is comparison of selected classification methods which are logistic regression (binary and multinominal), multilayer perceptron and classification trees, CHAID and CRT. The first part is reminiscent of the theoretical basis of these methods and explains the nature of parameters of the models. The next section applies the above classification methods to the six data sets and then compares the outputs of these methods. Particular emphasis is placed on the discriminatory power rating models, which a separate chapter is devoted to. Rating discriminatory power of the model is based on the overall accuracy, F-measure and size of the area under the ROC curve. The benefit of this work is not only a comparison of selected classification methods based on statistical models evaluating discriminatory power, but also an overview of the strengths and weaknesses of each method.
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