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Relationship between the use of alcohol and tobacco and subjective well-being among 6th graders
Černá, Michala ; Voňková, Hana (advisor) ; Gabrhelík, Roman (referee)
Mental health, integral part of the general health, has recently been increasingly associated with a term well-being. An alarming problem which occurs not only in Czech society is a high degree of early use of legal addictive substances (alcohol and tobacco) among children. This thesis provides an insight into the issue of the use of addictive substances by children in the context of subjective perception of personal well-being. Finding the prevalence of the use of these substances among children enabled the identification of links between the use and several factors which altogether represent subjective well-being. Satisfaction with oneself has proved insignificant in relation to substance abuse. Furthermore, it was found that children can compensate low self-esteem for alcohol. Based on these data using logistic regression there was designed a mathematical model which allows, while knowing the factors of personal well-being, the prediction of the probability of the use of tobacco and alcohol among children. Key words: prevention, substance abuse, well-being, alcohol, tobacco, logistic regression
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Recursive estimation of models relating discrete-valued variables to continuous-valued ones applied to trading with futures
Svoboda, Miroslav ; Kárný, Miroslav (advisor) ; Hurt, Jan (referee)
This bachelor thesis deals with recursive estimation of a dependence of the models with discrete variables on variables that are either discretely or continuously distributed. To this purpose Bayes formula, described in the first chapter, is used, to which an additional assumption of conditional independence is added so that it can be used dynamically. The second chapter describes an approximation algorithm, which is used for recursive approximation of the density of random variable that has been estimated by the Bayesian equation. The third chapter deals with the application of the whole model on a special form of logistic regression. Results are shown on the examples using simulated data. At last, the model along with approximation algorithm is applied on a trading with futures. Powered by TCPDF (www.tcpdf.org)
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Analysis of the Causes and Nature of Ethnic Conflicts
Kohout, Jan ; Plechanovová, Běla (advisor) ; Parízek, Michal (referee)
The aim of this thesis is to analyze factors responsible for onset of ethnic conflicts and selected characteristics. By comparing to non-ethnic conflicts it was determined, if there are any differences in onset mechanisms of these two types of conflicts and thus if there is a space for explanatory role of ethnicity as a cause of ethnic conflicts. Selection of examined factors is congruent with the relevant literature and existing analyses and reflects the context of contemporary conflict research. The influence of male unemployment rate, level of Human development index and its inequality-adjusted version, human rights and finally the influence of conflicts in neighbouring countries on the onset of conflict is tested by statistical methods in component analyses. Also the intensity of ethnic and non-ethnic conflicts, war years and HDI are also compared. The comparative style of the research helps to understand the true nature of causes of intrastate conflicts and indicates, that there is no difference between the two types. Empirical character of this thesis is also the reason for assessing it within the context of other quantitative studies of conflict, comparing the results and defining the proper level of analysis for reaching tangible contributions.
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Voters and Non-voters in the Czech Republic
Vavřinová, Tereza ; Linek, Lukáš (advisor) ; Hendl, Jan (referee)
This study discusses voting behavior of the citizens in The Czech republic. Traditional studies of voting behavior differentiate between voters and nonvoters according to their turnout in one election. This thesis takes up multielection approach and differentiates three categories of voting behavior- voters, nonvoters and irregular voters. Specific features of voters, nonvoters and irregular voters are identified using logistic regression analysis. Theoretically, the study is based on socioeconomic, motivational and mobilization theories of turnout. The focus is put on the decision making of irregular voters. Circumstances tied with irregular voters' turnout are identified. The discussion on methodological problems connected with multi-election approach and research of electoral behavior generally is part of the thesis. The Czech election study 2010 is a main source of the data for analysis.
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Discrimination measures in credit risk
Polak, Michal ; Pešta, Michal (advisor) ; Zahradník, Petr (referee)
Scoring models represent a fundamental tool for the modern management of credit risk. This is mainly due to a significant development in the field of information technology. Such models are used not only when providing credit, but also in strategies relating to the future management of credit risk, or in strategies connected with enforcing receivables. In my thesis I deal with discrimination measures used in the validation of diversification potential of logistic scoring models. At the beginning, I focus on the term 'risk'. Then, I introduce a basic division of scoring models. Next, I describe the method of scoring logistic regression, I concentrate on estimating parameters, their significance and on testing their relevance. For the measurement and illustration of diversification potential of the model I mention the most commonly used methods such as the Lorenz and ROC curve, the Gini coeficient, the c-statistic as well as the Kolmogorov-Smirnov test. Finally, I apply the theoretical knowledge to real data. I design a scoring model and subsequently compare the discrimination measures which it contains. Powered by TCPDF (www.tcpdf.org)
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Forecasting and nowcasting power of confidence indikators:Evidence for Central Europe
Herrmannová, Lenka ; Horváth, Roman (advisor) ; Mikolášek, Jakub (referee)
This thesis assesses the usefulness of confidence indicators for nowcasting and short term forecasting of the economic activity in the Czech Republic and three other Central European countries. The predictive power of both the Czech business confidence indicator and the customer confidence indicator is examined using two empirical approaches. First we predict the likelihood of economic downturn using logit models, later we estimate GDP growth out of sample forecasts in the framework of vector autoregression models. The results obtained from the downturn probability models confirm the ability of confidence indicators (especially the business confidence indicator) to estimate the current economic situation, so called nowcast. Results from the out-of-sample GDP growth value forecasting are ambiguous. Nevertheless the customer confidence indicator significantly improved original forecasts based on the model with standard macroeconomic variables and therefore we conclude in favour of its predictive power. Cross- country comparison confirms economic downturn nowcasting power of confidence indices in Hungary and Poland and fails to confirm such an ability of Slovak confidence indicators. One-quarter-ahead forecasts brought mixed results and therefore we conclude that nowcasting and forecasting properties of...
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Discrimination measures in credit risk
Polak, Michal ; Pešta, Michal (advisor) ; Zahradník, Petr (referee)
Scoring models represent a fundamental tool for the modern management of credit risk. This is mainly due to a significant development in the field of information technology. Such models are used not only when providing credit, but also in strategies relating to the future management of credit risk, or in strategies connected with enforcing receivables. In my thesis I deal with discrimination measures used in the validation of diversification potential of logistic scoring models. At the beginning, I focus on the term 'risk'. Then, I introduce a basic division of scoring models. Next, I describe the method of scoring logistic regression, I concentrate on estimating parameters, their significance and on testing their relevance. For the measurement and illustration of diversification potential of the model I mention the most commonly used methods such as the Lorenz and ROC curve, the Gini coeficient, the c-statistic as well as the Kolmogorov-Smirnov test. Finally, I apply the theoretical knowledge to real data. I design a scoring model and subsequently compare the discrimination measures which it contains. Powered by TCPDF (www.tcpdf.org)
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Lapse Analysis of Insurance Contracts
Strnad, Jan ; Mertl, Jakub (advisor) ; Mazurová, Lucie (referee)
The aim of the present work is to develop a tool for identification of Motor Third Party Liability insurance contracts which are at risk of cancellation. Methods for explorative data analysis, building a logistic regression model, comparing models and their validation and calibration are presented. Several models are developed on the real dataset using mentioned methods and then the final one is chosen. Behavior of the final model is verified by the validation on the out-of-time sample. Last step is calibration of the model to the expected value of the future portfolio cancellation rate.
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Application of (geo)demographic methods in education
Šebestík, Libor ; Hulíková Tesárková, Klára (advisor) ; Fialová, Ludmila (referee)
Application of (geo)demographic methods in education Abstract This master's thesis presents the possibilities of application of demographic, geodemographic and statistical methods on data published by the educational sector. The methods of demographic analysis are represented by the usage of rates, the concept of multistate demography (Markov chains) and the application of life tables. The enrollment ratio at particular levels of education, the average length of schooling and the number of dropouts from school grades are evaluated by these procedures. Markov chains which are based on the probabilities of transition between grades are also examined in terms of their use for forecasting purposes. These methods analyze the situation at the preschool, primary and secondary levels and are used on data from the annual Statistical Yearbooks on Education. In the field of geodemography, the so called preferential model of migration flows is presented. This model examines how applicants for tertiary education prefer or reject the regions of the Czech Republic for their tertiary education studies. The last method is the binary logistic regression which analyzes the inequalities in access to tertiary education. Both preferential model and logistic regression are based on data files on the admission process at...
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