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EN
Principal component analysis and factor analysis are the two most popular methods that allow to bring a large number of studied variables to a much smaller number of mutually independent principal components or factors. New variables (principal components or factors) retain a relatively large part of the information contained in the original variables, while each of them is a carrier of other substantive content. Both of these methods of reduction of the variables are often used, because too many pending attributes increases the range of the difficulty of interpretation. The main reason of undertaking the project is an attempt to show, that the abovementioned methods, although they are very similar, cannot be indentified. Despite the fact, that in both cases eigenvalues are calculated, factor loadings, etc., but still there are differences in the way of action, about which it must be remembered. So the usage of these names the variables are unacceptable. The article consists of three parts. The first and second chapter are devoted, respectively, to the analysis of the principal components and factor analysis, where a short characterization of these methods had been made. In the third chapter, on the basis of an empirical example, we compared the effectiveness of the principal components analysis and factor analysis.
EN
The aim of this paper is to show and compare different levels of risk during a day and during a week on spot markets from the Polish Power Exchange (POLPX) and the European Energy Exchange (EEX). Based on Principal Component Analysis (PCA) the classification of contracts from the two power exchanges was made. The classification was made for linear rates of return of 24 contracts listed on the power exchanges from 01.2009 to 24.10.2012. Additionally, the 24 contracts were divided into seven groups dependent on the day of a week. Based on these data sets the classification of risk during a week was made.
EN
The aim of this paper is to show and compare different levels of risk during a day and during a week on spot markets from the Polish Power Exchange (POLPX) and the European Energy Exchange (EEX). Based on Principal Component Analysis (PCA) the classification of contracts from the two power exchanges was made. The classification was made for linear rates of return of 24 contracts listed on the power exchanges from 01.2009 to 24.10.2012. Additionally, the 24 contracts were divided into seven groups dependent on the day of a week. Based on these data sets the classification of risk during a week was made.
XX
Zróżnicowanie regionalne krajów jest przedmiotem wielu badań i analiz. Celem artykułu jest ocena zróżnicowania regionalnego krajów tworzących Grupę Wyszehradzką. Wybór tych krajów wynikał z ich sąsiedztwa geograficznego, podobnej historii najnowszej, podobnej struktury gospodarki postsocjalistycznej i zbliżonych problemów społeczno-ekonomicznych. Analizę rozwoju regionalnego przeprowadzono dla regionów zgodnych z nomenklaturą NUTS 2. Tym samym porównaniu poddano 34 regiony. Do badania zastosowano zaproponowany w tym celu wskaźnik jakości rozwoju społeczno-ekonomicznego. Jest on obliczany na podstawie agregacji wyników analizy głównych składowych, którą przeprowadza się według macierzy korelacji standaryzowanych zmiennych - komponentów indeksu. Wartości wskaźnika rozwoju regionalnego obliczono osobno w ujęciu gospodarczym i społecznym. Umożliwiły one uporządkowanie regionów w różnych aspektach rozwoju, ocenę zmian rozwoju regionalnego w ujęciu dynamicznym oraz prognozowanie poziomu rozwoju. (fragment tekstu)
EN
The article contains the comparative analysis of the quality of regional development in Czech Republic, Poland, Slovakia and Hungary. The quality index of social and economic development has been proposed for this purpose which has been calculated on the basis of a certain aggregation of the results of Principal Component Analysis made on the correlation matrix of standardised variables being the components of the index. The calculated values of the index have allowed for ordering the regions of the Visegrad Group Countries in various aspects of regional development and the evaluation of changes in the development level from the dynamic perspective. Eurostat's Data has been used in calculations. (original abstract)
XX
W artykule przeprowadzono weryfikację koncepcji ekorozwoju powiatów woj. małopolskiego. W tym celu zaproponowano wskaźnik jakości rozwoju regionalnego. Obliczone wartości tego wskaźnika dla powiatów były podstawą do weryfikacji hipotezy o równowadze pomiędzy systemem gospodarczym, społecznym i ekologicznym. Wartości wskaźnika rozwoju wykorzystano również do oceny dynamiki zmian rozwoju. (fragment tekstu)
EN
The paper presents concept verification of the eco-development in powiats in the Małopolskie Voivodship. For this purpose the Regional Development Index was proposed which is based on an aggregation of the Principal Component Analysis results (using the correlation matrix of standardized variables). The values of the development indicator were calculated separately for the area of the socio-economic and the ecological development. The results have been used as the basis for verifying the hypothesis on the balance between social, economic and ecological systems. Development index values were also used to assess the dynamics of development and its prediction in the powiats of the Małopolskie Voivodship. (original abstract)
XX
Społeczeństwo informacyjne jest ważnym elementem strategii politycznej określającej kierunki rozwoju ekonomicznego oraz społecznego państw i regionów. Wraz z rozwojem społeczeństwa informacyjnego i wzrostem wykorzystywania nowoczesnych technologii informacyjnych i komunikacyjnych (ICT), pojawiło się zjawisko wykluczenia informacyjnego. Zmniejszenie tych różnic i wzrost e-dostępności to priorytety polityki UE na rzecz rozwoju regionalnego i e-integracji. Zestawiono wartości podstawowych miar statystycznych dla przyjętych wskaźników w analizie porównawczej poziomu rozwoju społeczeństwa informacyjnego między krajami UE w latach 2007 i 2009. Analiza została przygotowana na podstawie danych z bazy Eurostat.
EN
The information society is an important element of EU political strategies of the social and economic development of countries and regions. Together with the development of the information society and increasing use of modern Information and Communication Technologies, the digital divide appeared as a new inequality type between different units. The reduction of digital divide and increase of e-availability are priorities of EU policy for regional development and e-integration. In the article quantitative methods (principal component analysis, biplot, synthetic measures of development, S-time distance) are applied to evaluation of inequalities in the level of information society development between EU countries in 2007 and 2009 years. The analysis was prepared on the Eurostat data base. (original abstract)
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