Multivariate statistical analysis of environmental data

Justyna Brzezińska , Aneta Rybicka , Marcin Pełka

Abstract

One of the characteristics of environmental data is that many of them are mostly described by complex and large number of variables. To understand this phenomena it is necessary to analyze the relationship and association between them. In this paper we apply multivariate statistical methods for the analysis of environmental problems. The main aim of the paper is to present an application of the linear ordering with multidimensional scaling for results visualization in the environmental data (green growth) analysis. The main contribution of this paper is the empirical part of this paper will that presents the application of linear ordering several multivariate methods and graphical presentation using modern and advanced visualizing tools based on datasets and reports from the Organization for Economic Cooperation and Development (OECD). Presented analysis may be used in all types of environmental practice and real life solutions. All calculations will be conducted done in R software using.
Author Justyna Brzezińska
Justyna Brzezińska,,
-
, Aneta Rybicka (EMaT / DEaCS)
Aneta Rybicka,,
- Department of Econometrics and Computer Science
, Marcin Pełka (EMaT / DEaCS)
Marcin Pełka,,
- Department of Econometrics and Computer Science
Pages40-49
Publication size in sheets0.5
Book Papież Monika, Śmiech Sławomir (eds.): The 12th Professor Zelias International Conference on Modelling and Forecasting of Socio-Economic Phenomena. Conference Proceedings, Socio-Economic Modelling and Forecasting, no. 1, 2018, Fundacja Uniwersytetu Ekonomicznego w Krakowie, ISBN 9788365907202, 611 p., DOI:10.14659/SEMF.2018.01
Keywords in Englishenvironmental data, multivariate statistical analysis, R software
DOIDOI:10.14659/SEMF.2018.01.04
URL http://www.semf.pl/semf_1/pdf/Brzezinska_Rybicka_Pelka.pdf
Languageen angielski
File
Brzezinska_Rybicka_Pelka_Multivariate_statistical_analysis_of_environmental.pdf 380,36 KB
Score (nominal)20
ScoreMinisterial score = 20.0, 06-11-2019, ChapterFromConference
Citation count*
Cite
Share Share

Get link to the record


* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
Back