|
|
Visual statistical inference
Jeliga, Jan ; Hlávka, Zdeněk (advisor) ; Maciak, Matúš (referee)
Graphs, and data visualization in general, play a important role in modern statistics. In this thesis, we address the possibility of using these for hypothesis testing. First, we introduce the concept of visual testing and define analogies for terms such as statistic or p-value and additionally we define the terms specific to visual testing. We demonstrate the method of visual testing on an example, where we parallelly perform a conventional test for the same data set and the same null and alternative hypothesis. Further, we inspect the possibility of use of Amazon Mechanical Turk for visual testing. We describe the design of visual test and present results of simulation experiments conducted in order to assess the power of the visual test and to compare it to conventional test. Powered by TCPDF (www.tcpdf.org)
|
|
|
Analysis of the Quality of life using cluster analysis and comparison with the Human Development Index
Pánková, Barbara ; Miskolczi, Martina (advisor) ; Langhamrová, Jana (referee)
Nowadays quality of life is often discussed topic. In defining this term, there is considerable ambiguity and disunity, since there is no universally accepted definition, nor theoretically sophisticated model. However, despite this fact, the level of quality of life is currently one of the most discussed topic. Monitoring the quality of life by using a variety of indicators are engaged in several international organizations, one of them is the Development Programme of the United Nations. This organization annually publishes the Human Development Index, which divides the world´s countries into four groups according to their level of development: low, medium, high and very high development. The aim of this thesis is to analyze the quality of life in 125 countries by using cluster analysis, accurately the Ward's method. Quality of life in this thesis is evaluated based on 19 demographic and economic indicators, which include life expectancy, literacy rate, access to drinking water and infant mortality rate. The cluster analysis divided the country into individual clusters by their similarities. Six clusters were created by this analysis, which had been compared with the results of Human Development Index. The clusters very well reflect the division, which is commonly used in the characterization of developing and developed countries. Each of the six clusters can be very well described and characterized in terms of quality of life. It is also possible qualify those clusters as poorest developing, low developed, moderately developed, medium development, high and very high development countries. Based on the results it can be stated that this analysis is consistent with other indicators of quality of life and the resulting clusters are identical with the division of countries which is commonly used.
|
|
|
Life tables analysis using selected multivariate statistical methods
Bršlíková, Jana ; Vilikus, Ondřej (advisor) ; Miskolczi, Martina (referee)
The mortality is historically one of the most important demographic indicator and definitely reflects the maturity of each country. The objective of this diploma thesis is the comparison of mortality rates in analyzed countries around the world over time and among each other using the principle component analysis that allows assessing data different way. The big advantage of this method is minimal loss of information and quite understandable interpretation of mortality in each country. This thesis offers several interesting graphical outputs, that for example confirm higher mortality rate in Eastern European countries compared to Western European countries and show that Czech republic is country where mortality has fallen most in context of post-communist countries between 1990 and 2010. Source of the data is Human Mortality Database and all data were processed in statistical tool SPSS.
|
|
|
Scoring methods used in cluster analysis
Sirota, Sergej ; Löster, Tomáš (advisor) ; Makhalova, Elena (referee)
The aim of the thesis is to compare methods of cluster analysis correctly classify objects in the dataset into groups, which are known. In the theoretical section first describes the steps needed to prepare a data file for cluster analysis. The next theoretical section is dedicated to the cluster analysis, which describes ways of measuring similarity of objects and clusters, and dedicated to description the methods of cluster analysis used in practical part of this thesis. In practical part are described and analyzed 20 files. Each file contains only quantitative variables and sort characters by which objects are sorted. In each file is calculated success rate of object segmentation into groups for each cluster method. At the end of the practical part is a summary description of the results of cluster methods. The main contribution of this thesis is to evaluate the success of cluster methods for classification objects into known groups.
|
|
|
Use of statistical methods in rating applicants for vacancies
Rabochová, Lucie ; Vrabec, Michal (advisor) ; Svoboda, Libor (referee)
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.
|
guest ::
