A systematic review examining the assumptions of statistical methods used in scientific and technology research
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Abstract
Statistical hypothesis testing requires the checking of assumptions in order to achieve valid and reliable research results. This study aimed to examine the reporting of statistical assumptions checking in scientific and technology research. A total of 126 research articles were searched in two scientific and technology journals published in 2021-2023, and data from research articles using inferential statistics was synthesized. Five commonly used statistical methods were considered. - t-test (independent samples t-test and paired samples t-test), one-way analysis of variance, chi-squared test, and Pearson correlation coefficient. The results showed that out of 126 research articles, 58 used inferential statistics (46.03% of all research articles and 59.18% of empirical research articles). The most used analytical statistic was one-way ANOVA, 34 articles (26.98% of all empirical research articles using inferential statistics), followed by independent samples t-test and Pearson correlation coefficient of 5 articles (3.97%), and chi-squared test of 3 articles (2.38%). Based on empirical research articles using inferential statistics to analyze data, only 4 articles (6.9%) reported the checking of statistical assumptions.
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References
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