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Comparison of Parametric and Nonparametric Test Results: Asian Demographics as Database

Several studies used both parametric and nonparametric tests in the statistical analysis of data. A number of findings revealed varied results when both treatments were applied. In most cases, differences were due to wrong assumptions of normality of data distribution, the insufficient sample size, the inappropriate type of variables employed, etc. With these disparities, the researcher investigated the outcomes of the parametric and nonparametric tests if their respective data requirements are met and no assumptions are violated. To show fairness in handling data and procedure, the researcher used the published data on South-East Asian demographics. Data were subjected to normality test using the normal probability plot and Kolmogorov-Smirnov test. Other data requirements were taken into account before the parametric and nonparametric statistics were applied. The parametric tests employed in this research are: (1) t-test for two correlated samples; (2) t-test for two uncorrelated samples; (3) analysis of variance or F-test for three samples; and (4)Pearson r for two correlated variables; with their corresponding nonparametric