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Using goodness-of-fit tests to detect normality for mesokurtic data

Mini Dissertation (MSc (Advanced Data Analytics))--University of Pretoria, 2023.

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Other Authors: Van Staden, Paul J.
Format: Thesis
Language:English
Published: University of Pretoria 2023
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access_status_str Open Access
author2 Van Staden, Paul J.
author_browse Van Staden, Paul J.
author_facet Van Staden, Paul J.
collection Thesis
dc_rights_str_mv © 2022 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
description Mini Dissertation (MSc (Advanced Data Analytics))--University of Pretoria, 2023.
format Thesis
id oai:repository.up.ac.za:2263/89422
institution University of Pretoria (South Africa)
language English
last_indexed 2026-06-10T12:38:48.199Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2023
publishDateRange 2023
publishDateSort 2023
publisher University of Pretoria
publisherStr University of Pretoria
record_format dspace
source_str UPSpace — University of Pretoria Institutional Repository
spelling oai:repository.up.ac.za:2263/89422 Using goodness-of-fit tests to detect normality for mesokurtic data Van Staden, Paul J. micaelasclanders@outlook.com Sclanders, Micaela Lee UCTD Goodness-of-fit tests Mesokurtosis Normal distribution Power comparison Ultra-marathon race times Mini Dissertation (MSc (Advanced Data Analytics))--University of Pretoria, 2023. The normality assumption is crucial in statistical inference and modelling. It is therefore important to determine if a sample comes from a normal distribution. Consequently, numerous goodness-of-fit hypothesis tests have been developed. The practical use of a specific test depends on its availability in the statistical software package considered. The field of application will also contribute to the choice of test. For instance, the Jarque-Bera test is popular in econometrics and finance. Various power comparison and simulation studies of goodness-of- t tests for normality can be found in the literature. Typically, these studies select alternative distributions whose levels of skewness and kurtosis deviate from that of the normal distribution. I.e., symmetric and asymmetric distributions exhibiting leptokurtosis or platykurtosis are included in these simulation studies. In this mini-dissertation, the focus is on mesokurtic distributions whose levels of skewness and kurtosis are equivalent to that of the normal distribution, but with different distributional shapes compared to the normal distribution. Statistics MSc (Advanced Data Analytics) Unrestricted 2023-02-10T13:47:23Z 2023-02-10T13:47:23Z 2023 2023 Mini Dissertation * A2023 https://repository.up.ac.za/handle/2263/89422 en © 2022 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria
spellingShingle UCTD
Goodness-of-fit tests
Mesokurtosis
Normal distribution
Power comparison
Ultra-marathon race times
Using goodness-of-fit tests to detect normality for mesokurtic data
title Using goodness-of-fit tests to detect normality for mesokurtic data
title_full Using goodness-of-fit tests to detect normality for mesokurtic data
title_fullStr Using goodness-of-fit tests to detect normality for mesokurtic data
title_full_unstemmed Using goodness-of-fit tests to detect normality for mesokurtic data
title_short Using goodness-of-fit tests to detect normality for mesokurtic data
title_sort using goodness of fit tests to detect normality for mesokurtic data
topic UCTD
Goodness-of-fit tests
Mesokurtosis
Normal distribution
Power comparison
Ultra-marathon race times
url https://repository.up.ac.za/handle/2263/89422