Evaluation of statistical methods applied in theses and dissertations in an Open, Distance and e-Learning University

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Vydáno v:PLoS One vol. 20, no. 3 (Mar 2025), p. e0319654
Hlavní autor: Legesse Kassa Debusho
Další autoři: Mashabela, Mahlageng Retang, Sebatjane, Phuti Naphtaly, Sithole, Sthembile, Tabo, Busisiwe, Eeva-Maria Rapoo
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Public Library of Science
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100 1 |a Legesse Kassa Debusho 
245 1 |a Evaluation of statistical methods applied in theses and dissertations in an Open, Distance and e-Learning University 
260 |b Public Library of Science  |c Mar 2025 
513 |a Journal Article 
520 3 |a The appropriate application of research methods and statistical analyses used in the studies directly affects the quality of scientific studies. Due to the possibility of employing an incorrect statistical technique, it is crucial to choose a statistical method based on the study’s data and research objectives. This study aimed to evaluate whether statistical techniques applied in the theses and dissertations were appropriate for planning surveys or experiments and analyzing data, and to identify common mistakes that master’s and doctoral students made when using statistical techniques for the intended goals. The study reviewed 139 master’s theses and doctoral dissertations submitted to seven agricultural and environmental sciences disciplines at a leading Open, Distance and e-learning university in Africa between 2015 and 2020. These dissertations and theses used mixed and quantitative research methods. The analysis of variance test was the most often used statistical test, according to the results, followed by the student t-test and the Chi-square test. At least one blatant methodological error was found in 41.0% of theses and dissertations, either in the data collection process or in the data analysis. Examples of these errors include the use of a simple random sampling technique despite the heterogeneous population units, the conversion of count responses to binary responses and percentages for fitting logistic and general binomial regression models, and the incorrect modeling of correlated data using generalized linear models. The results of this study will create greater awareness of the common errors that postgraduate students make when using statistical methods to design experiments or sample surveys and analyse data. In addition, the findings inform the university management to plan for specific training in statistical methods appropriate for a range of academic fields. 
651 4 |a Africa 
653 |a Regression models 
653 |a Environmental science 
653 |a Data collection 
653 |a Regression analysis 
653 |a Statistical tests 
653 |a Questionnaires 
653 |a Data analysis 
653 |a Random sampling 
653 |a Sampling techniques 
653 |a Theses 
653 |a Quantitative research 
653 |a Colleges & universities 
653 |a Statistical analysis 
653 |a Sample size 
653 |a Hypotheses 
653 |a Statistical sampling 
653 |a Research methods 
653 |a Online instruction 
653 |a Statistical methods 
653 |a Errors 
653 |a Statistical models 
653 |a Learning 
653 |a Institutional repositories 
653 |a Design of experiments 
653 |a Dissertations & theses 
653 |a Chi-square test 
653 |a Students 
653 |a Dissertations 
653 |a Research methodology 
653 |a Variance analysis 
653 |a Sampling methods 
653 |a Surveys 
653 |a Distance learning 
653 |a Graduate students 
653 |a Social 
700 1 |a Mashabela, Mahlageng Retang 
700 1 |a Sebatjane, Phuti Naphtaly 
700 1 |a Sithole, Sthembile 
700 1 |a Tabo, Busisiwe 
700 1 |a Eeva-Maria Rapoo 
773 0 |t PLoS One  |g vol. 20, no. 3 (Mar 2025), p. e0319654 
786 0 |d ProQuest  |t Health & Medical Collection 
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