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The applicability of discriminant analysis techniques on the multivariate normal and non-normal data types in marketing research.

Includes bibliography.

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Bibliographic Details
Main Author: Van Deventer, Petrus Jacobus Uys
Other Authors: Troskie, Casper G
Format: Thesis
Language:English
Published: Department of Mathematics and Applied Mathematics 2014
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access_status_str Open Access
author Van Deventer, Petrus Jacobus Uys
author2 Troskie, Casper G
author_browse Troskie, Casper G
Van Deventer, Petrus Jacobus Uys
author_facet Troskie, Casper G
Van Deventer, Petrus Jacobus Uys
author_sort Van Deventer, Petrus Jacobus Uys
collection Thesis
description Includes bibliography.
format Thesis
id oai:open.uct.ac.za:11427/4941
institution University of Cape Town (South Africa)
language eng
last_indexed 2026-06-10T12:32:52.713Z
license_str Not specified — see source repository
provenance_str_mv Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository
publishDate 2014
publishDateRange 2014
publishDateSort 2014
publisher Department of Mathematics and Applied Mathematics
publisherStr Department of Mathematics and Applied Mathematics
record_format dspace
source_str UCTD — University of Cape Town Open Access Repository
spelling oai:open.uct.ac.za:11427/4941 The applicability of discriminant analysis techniques on the multivariate normal and non-normal data types in marketing research. Van Deventer, Petrus Jacobus Uys Troskie, Casper G Applied Mathematics Includes bibliography. The purpose of the procedures described is to assign “objects” or "observations" in some optimum fashion to one of two or more populations. In routine banking a bank manager may wish to classify clients who wish to make loans as low or high credit risks on the basis of the elements of certain accounting statements. In such a case there are two definite distinct classes. Another investigation may be initiated to determine whether buying habits are different with respect to the categories: urban, sub-urban and rural clients. Note that in the first example the classes are determined before any sample of observations is investigated, i.e. the sample results do not influence the choice of groups. In the latter case one is trespassing on the terrain of cluster analysis.In the first case we have two types of problems, namely that of devising a classification rule from samples of already classified objects and that of imposing the classification scheme on the objects. The term "discrimination" refers to the process of deriving classification rules from samples of classified objects and the term "classification" refers to applying the rules to knew objects of unknown class. Although it is possible to convert raw data into more easily grasped forms like cartoon faces (Chernoff, 1973) this still represents the problem that any grouping or classification based on these diagrams is subjective. 2014-07-31T08:11:09Z 2014-07-31T08:11:09Z 1985 Master Thesis Masters MSc http://hdl.handle.net/11427/4941 eng application/pdf Department of Mathematics and Applied Mathematics Faculty of Science University of Cape Town
spellingShingle Applied Mathematics
Van Deventer, Petrus Jacobus Uys
The applicability of discriminant analysis techniques on the multivariate normal and non-normal data types in marketing research.
thesis_degree_str Master's
title The applicability of discriminant analysis techniques on the multivariate normal and non-normal data types in marketing research.
title_full The applicability of discriminant analysis techniques on the multivariate normal and non-normal data types in marketing research.
title_fullStr The applicability of discriminant analysis techniques on the multivariate normal and non-normal data types in marketing research.
title_full_unstemmed The applicability of discriminant analysis techniques on the multivariate normal and non-normal data types in marketing research.
title_short The applicability of discriminant analysis techniques on the multivariate normal and non-normal data types in marketing research.
title_sort applicability of discriminant analysis techniques on the multivariate normal and non normal data types in marketing research
topic Applied Mathematics
url http://hdl.handle.net/11427/4941
work_keys_str_mv AT vandeventerpetrusjacobusuys theapplicabilityofdiscriminantanalysistechniquesonthemultivariatenormalandnonnormaldatatypesinmarketingresearch
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