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Determination of factors that influence digit preference: A Case study of South African Census 2011 Age-Sex date

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dc.contributor.advisor Kyei, K. A.
dc.contributor.advisor Moyo, S.
dc.contributor.author Netshiozwi, Masala
dc.date 2020
dc.date.accessioned 2021-02-02T13:34:49Z
dc.date.available 2021-02-02T13:34:49Z
dc.date.issued 2020-01
dc.identifier.citation Netshiozwi, Masala (2020) Determination of factors that influence digit preference: A Case study of South African Census 2011 Age-Sex date. University of Venda, South Africa. <http://hdl.handle.net/11602/1663>.
dc.identifier.uri http://hdl.handle.net/11602/1663
dc.description MSc (Statistics) en_ZA
dc.description Department of Statistics
dc.description.abstract The age distribution of a population is one of the most important demographic factors that plays a major role in describing and making projections about the population. Age distribution determine life expectancy, fertility and migration. It suffers most of the difficulties with regard to its accuracy, due to age misstatement and other factors. The study sought to determine the factors that influence digit preference in Age data using the South African census 2011 Age-sex data. Various methods were applied to examine the objectives of the study. The Visual Inspection methods (Line graph and Population Pyramid), Statistical methods (Age Ratio and Sex Ratio) and multivariate methods (Generalized linear model, Principal Component analysis and Regression analysis) which have been reviewed in detail in the study. This study utilized a full age dataset in single years. Based on the United Nation Age-sex Accuracy Index which was found to be 18.3, it shows that the data collected was of good quality. Besides the results deduced from the analysis to determine the quality of data, the study found that education level, place of residence, gender and ethnic group are the factors that influence digit preference. This was provided as evidence by calculated p-values <0.05, showing a positive relationship for generalized linear model. Principal component analysis and Regression analysis confirm the findings by Generalized linear model en_ZA
dc.description.sponsorship NRF en_ZA
dc.format.extent 1 online resource (x, 76 leaves : color illustrations, color maps)
dc.language.iso en en_ZA
dc.rights University of Venda
dc.subject Age heaping en_ZA
dc.subject Age-Sex Accuracy Index en_ZA
dc.subject Digit preference and Education en_ZA
dc.title Determination of factors that influence digit preference: A Case study of South African Census 2011 Age-Sex date en_ZA
dc.type Dissertation en_ZA


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