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Personal GPS Track Database
Šrubařová, Daniela ; Bartík, Vladimír (referee) ; Burget, Radek (advisor)
The main goal of this thesis is to design and implement an application serving as a database of routes recorded by GPS devices and for purposes of personal use in sport activities such as cycling and running. Proces of both design and implementation is described. The resulting application is capable of processing the files containing data in GPX format. These records can be visualised with support provided by Google maps service. All the useful information about routes is well-aranged and displayed to the user. The application computes statistics for a chosen period of time and provides graphs of elevation profile for selected route. Implemented system for the route management has been continuously tested by volunteers and thus became user-friendly with intuitive user interface.
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Dependence Measures
Janda, Radek ; Fusek, Michal (referee) ; Michálek, Jaroslav (advisor)
This thesis focuses on characteristics of the dependence measures among random quantities, as well as its use in industry. The theoretical part focuses on examples of the characteristics used. Furthermore, the software Statistica is described here, for its possibilities of implementing such characteristics. On simple examples, the use of dependence measures is shown. In the practical part, the thesis focuses on statistical analysis of real industrial data, whilst implementing the theory mentioned above.
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Evaluating a Structural Model Forecast: Decomposition Approach
Brázdik, František ; Humplová, Zuzana ; Kopřiva, František
Macroeconomic forecasters are often criticized for a lack of transparency when presenting their forecasts. To deter such criticism, the transparency of the forecasting process should be enhanced by tracing and explaining the effects of data revisions and expert judgment updates on variations in the forecasts. This paper presents a forecast decomposition analysis framework designed to examine the differences between two forecasts generated by a linear structural model. The differences between the forecasts considered can be decomposed into the contributions of various forecast elements, such as the effect of new data or expert judgment. The framework allows us to evaluate the contributions of forecast assumptions in the presence of expert judgment applied in the expected way. The simplest application of this framework examines alternative forecast scenarios with different forecast assumptions. Next, a one-period difference between the forecasts’ initial periods is added to the examination. Finally, a replication of the Inflation Forecast Evaluation presented in Inflation Report III/2013 is created to illustrate the full capabilities of the decomposition framework.
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The development of the employment of the manufacturing industry in the South Bohemian region from 1930 to 2011
JEŘÁBKOVÁ, Šárka
The bachelor thesis deals with the development of the employment rate of the manufacturing industry in the South Bohemian region. The development is monitored from 1930, because of the unavailability of the older statistical data. The year 2011 is the last monitored year. The last statistical census was in 2011. There are eight profile years, which were established according to the census taken in the region of Czech Republic, with the exception of the year 1989, because of the availability of the more detailed data for this year. The methodology of the thesis is very important, due to the disunity of the statistic and counting methods. The thesis is concerned with the region of the South Bohemia. There are seven districts now, but there were some changes in the history. The development of the historical administrative division is also included in the thesis. Whole work is completed with the charts, diagrams and maps.
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Competing on Analytics
Nagin, Gleb ; Pour, Jan (advisor) ; Basl, Josef (referee)
Business analytics refers to the skills, technologies, applications and practisies for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods. Business intelligence traditionally focuses on using a consistent set of metrics to both measure past performance and guide business planning, which is also based on data and statistical methods. Analytics makes extensive use of data, statistical or quantitative analyses, explanatory and predictive modeling, and fact based management to drive decision, making. Analytics may be used as input for human decisions or may drive fully automated decisions. In other words, querying, reporting, OLAP, and alert tools can answer questions such as what happened, how many, how often, where the problem is, and what actions are needed. Business analytics can answer questions like why is this happening, what if these trends continue, what will happen next, what is the best that can happen (optimize). Example of application analytics in different areas: banks use data analyses to differentiate among customers based on credit risk, usage of other characteristics with appropriate product offering. Harrah's company (from 2010 renamed and called Caesers entertaiment. Gaming corporation that owns and operate over 50 casinos, hotels, and seven golf courses under several brands), uses analytics for customer loyalty programs. Deere & Company (manufacturer of agricultural machinery like tractors, combine harvesters, sprayers and other) saved more than $1 billion by employing and implementing a new analytical tool to better optimize inventory. We can mention areas where within analytics are basic domain model: sales/retail business, financial services, risk & credit, marketing, fraud, pricing, telecommunications, supply chain, transportation and many others.
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Návrh systému hodnocení politik mezi jednotlivými systémy uživatelských informací ve vazbě na efektivní využití výsledků na rozhodovací a informační chování podle modelů a principů udržitelného rozvoje včetně testování a prezentace nástrojů znalostní báze životního prostředí
Ing. Lubomír Nondek, CSc. ; CENIA, česká informační agentura životního prostředí ; Bartoš, Lubomír ; Rollerová, Miluše ; Kodetová, Alžběta ; Cikánková, Jarmila ; Fereš, Jaroslav ; Valta, Jiří ; Kobližková, Edita ; Helová, Simona ; Matoušková, Leona ; Mertl, Jan ; Olivová, Lenka ; Pokorný, Jan ; Doubrava, Pavel ; Nondek, Lubomír
Zpráva popisuje výstupy projektu, jehož cílem bylo navržení ucelené metodické a institucionální základny, která bude vytvářet podklady pro rozhodování, přípravu strategických materiálů a umožní vypracovávat scénáře vývoje životního prostředí. Součástí projektu je návrh hodnocení vytvořených koncepčních materiálů. V rámci projektu byl vypracován přehled standardních technik rozhodování, ověřena aplikovatelnost metody analýzy obalu dat (DEA) a testovány analýzy časových řad. Byl připraven návrh na propojení práce expertů při přípravě pravidelně vydávaných zpráv o stavu životního prostředí a při práci na tvorbě výhledů a scénářů. Byl vypracován návrh na vytvoření pracovní skupiny a koordinačního centra GAINS CENIA pro analýzu scénářů politiky životního prostředí a jeho propojení se souvisejícími aktivitami. Byly zkoumány modely GAINS a LCA model IWM-2. Zpráva obsahuje podrobnější popis výsledků v jednotlivých přílohách.
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Sources of statistical data
Lepša, Ondřej ; Sobíšek, Lukáš (advisor) ; Vintr, Tomáš (referee)
The aim of this bachelor thesis is to describe statistical data, processes which lead to the gathering of such data and their usability in practical use. That is achieved by own research of publicly accessible sources of statistical data and companies that provide services in this area. The goal is to simplify orientation of economical subjects in situations wherein is appropriate to use statistical data. The structure of the thesis is divided into four parts. The first part defines the basic principals of statistical data and surveying. The second part devotes to non commercial sources of statistical data, third part addresses to commercial companies that gather statistical data and evaluate them. The last part concerns gathering and processing of company's own statistical data. This part is supplemented by an analysis of a particular survey made by existing company.
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