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Multivariate data analysis for monitoring the quality of the commercialized bottled water in Bangladesh

Bibliographic Details
Main Author: Anwar, K M Mostafa
Publication Date: 2018
Format: Master thesis
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/40334
Summary: Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and Management
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spelling Multivariate data analysis for monitoring the quality of the commercialized bottled water in BangladeshChemometricsPattern RecognitionPrincipal Component AnalysisFactor AnalysisCluster AnalysisBottled Water Quality MonitoringMarket SurveillanceDissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and ManagementSeveral multivariate statistical or chemometrics or pattern recognition techniques e.g. Principal Component Analysis, Factor Analysis, Hierarchical and Non-Hierarchical k-Mean Cluster Analysis have been applied to gain understanding about the quality of the packaged bottled drinking water in the market of Bangladesh. Twenty three (23) physico-chemical properties of total of 51 water samples have been investigated. The data set consists of 49 individuals from 11 Brands and 2 deionized ASTM TYPE-I water samples produced in the laboratory to be a technically pure water having Electrical Conductivity ~0.056 μS-cm-1. Descriptive statistics, analysis of variance, Non-Parametric Kruskal-Wallis tests have been conducted to detect statistical differences between the water types and different brands. Total of 23 attributes of water covering major ion contents: sodium, potassium, calcium, magnesium, iron, manganese, chloride, fluoride, sulphate, bicarbonate and nitrate and other features: pH, temperature, total dissolved solids, electrical conductivity, hardness, ammonium, nitrite, free cyanogen and chemical oxygen demand, total cation sum and total anion sum. Both the Principal Components Analysis and the Factor Analysis revealed that the differences between water individuals are best characterized by four Principal Components or Factors indicating material loadings, hardness or softness aesthetic acceptability and lightness/sutability for human consumption. Hierarchical and Non- Hierarchical k-means Cluster Analysis clearly identified the presence of four distinct clusters: A, B, C and D among the bottled water products in the market of Bangladesh. The profile features for each cluster have been defined as such the classification achieved to acquire improved and detailed understanding of the general properties of the products under study. We have observed that HCA using WARD algorithm provided us with more realistic classification solution in comparison with non-hierachical k-means as the Cluster members are truly reflecting their group pattern in line with their chemical compositions. HCA using WARD showed that BRAND05 and BRAND11 belonging to Cluster A products execssively loaded with materials and considered to be as hard waters. And BRAND09 and BRAND10 staying with DEIONIZEDWATER belonging to Cluster B are completely devoide of essential minerals as such seemed to be as ultra low mineral content type water or too soft in nature. The other folks BRAND03, BRAND04, BRAND06, BRAND07 and BRAND08 are also not having sufficient mineral contents so as to be very soft water indeed. Hence, waters belonging to Clusters A, B and C are not suitable for human consumption. Only two brands BRAND01 and BRAND02 staying in Cluster D appeared to be suitable for human consumption in every respect.The fact is the BRAND01 is produced by a foreign manufacturer. That means, all other local brands, except BRAND02 are essentially not having the appropriate quality to be drinking waters. From both PCA and FA these two brands BRAND01 and BRAND02 have been very well explained. These are the major outcomes of this study not immediately apparent from univariate approach or not appeared from the data set while looking through naked eyes. It is revealed that the multivariate data analytical techniques have potential to be useful complementary techniques to support the existing univariate practices for industrial quality assurance quality control, market surveillance, standardization process and or regulatory purposes and also seemed to be interesting to academic and scientific communities seeking advanced knowledge.Gomes, Paulo Jorge Mota de PinhoRUNAnwar, K M Mostafa2018-06-27T16:46:26Z2018-06-262018-06-26T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/40334TID:201948249enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T17:33:39Zoai:run.unl.pt:10362/40334Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:04:40.722791Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Multivariate data analysis for monitoring the quality of the commercialized bottled water in Bangladesh
title Multivariate data analysis for monitoring the quality of the commercialized bottled water in Bangladesh
spellingShingle Multivariate data analysis for monitoring the quality of the commercialized bottled water in Bangladesh
Anwar, K M Mostafa
Chemometrics
Pattern Recognition
Principal Component Analysis
Factor Analysis
Cluster Analysis
Bottled Water Quality Monitoring
Market Surveillance
title_short Multivariate data analysis for monitoring the quality of the commercialized bottled water in Bangladesh
title_full Multivariate data analysis for monitoring the quality of the commercialized bottled water in Bangladesh
title_fullStr Multivariate data analysis for monitoring the quality of the commercialized bottled water in Bangladesh
title_full_unstemmed Multivariate data analysis for monitoring the quality of the commercialized bottled water in Bangladesh
title_sort Multivariate data analysis for monitoring the quality of the commercialized bottled water in Bangladesh
author Anwar, K M Mostafa
author_facet Anwar, K M Mostafa
author_role author
dc.contributor.none.fl_str_mv Gomes, Paulo Jorge Mota de Pinho
RUN
dc.contributor.author.fl_str_mv Anwar, K M Mostafa
dc.subject.por.fl_str_mv Chemometrics
Pattern Recognition
Principal Component Analysis
Factor Analysis
Cluster Analysis
Bottled Water Quality Monitoring
Market Surveillance
topic Chemometrics
Pattern Recognition
Principal Component Analysis
Factor Analysis
Cluster Analysis
Bottled Water Quality Monitoring
Market Surveillance
description Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and Management
publishDate 2018
dc.date.none.fl_str_mv 2018-06-27T16:46:26Z
2018-06-26
2018-06-26T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/40334
TID:201948249
url http://hdl.handle.net/10362/40334
identifier_str_mv TID:201948249
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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