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The normality test and homogeneity test are two essential stages in quantitative research data analysis. The normality test is used to determine whether research data are normally distributed, which serves as the basis for deciding whether to apply parametric or nonparametric statistical tests. Several parametric analyses, such as linear regression, ANOVA, ANCOVA, and MANOVA, require normally distributed data to ensure valid results. Meanwhile, the homogeneity test aims to determine whether the variances of data across groups being compared are homogeneous or consistent. Data homogeneity is also a primary prerequisite for using certain parametric tests, particularly those involving more than one sample group. Therefore, understanding both tests is crucial for researchers to select the appropriate analytical methods and to obtain research results that are scientifically accountable.