<![CDATA[Quantitative research requires accurate statistical analysis to ensure that the results obtained are valid and scientifically accountable. One important stage in statistical analysis is assumption testing, particularly normality and homogeneity tests, which are prerequisites for the use of parametric statistical methods. This article aims to discuss the concepts, roles, and applications of normality and homogeneity tests in statistical analysis. The research method used is qualitative research with a li brary research approach through the study of statistical textbooks and relevant national and international journal articles. The results of the discussion show that the normality test plays a role in ensuring that the data distribution approximates a normal distribution, while the homogeneity test is used to ensure the uniformity of variance between data groups. Fulfilling these two assumptions allows researchers to use parametric statistical techniques appropriately and reduce the risk of bias in the analysis. Thus, a good understanding of normality and homogeneity tests is very important to improve the quality of data analysis and the accuracy of research conclusions.]]>
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