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African Journal of Mathematics and Statistics Studies
Vol. 8Issue 12025pp. 198–208Published 25 March 2025
DOI 10.52589/AJMSS_V0SUHL6WResearch Article
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Abstract:
The Ordinal scale of measurement is not understood by many researchers, especially in the social and business fraternities. The thinking that coding values of ordinal scale variables converts data from being qualitative into being quantitative is held by these researchers. A sample of randomly selected articles on factors affecting students’ academic performance is studied to establish how ordinal level variables are analyzed. Results show that the greater part of researchers do not know that, although it is correct that where there is quantity there is number, the converse is incorrect. Parametric techniques dominate in the analysis of ordinal data. Scenarios are forwarded for purposes of sending home the message of differentiating when number is quantity and when it is not. Techniques that are designed for the analysis of ordinal data are then shared.
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