Analysis Of 4.5 Kruskal-Wallis Test

4.5 Kruskal-Wallis Test
Based on the normality test that was done, it was shown that the data were not normally distributed so a non-parametric test has to be done instead of a parametric test. Kruskal-Wallis’ test (also called the one-way ANOVA on ranks), was done to determine if there were statistically significant differences between three groups of an independent variable on a continuous variable.
4.5.1 Compare mean AA among the three races in both age groups
The Kruskal-Wallis test was done to compare the mean AA among the Malay, Chinese, and Indian races in the age group of 20-29. Significance value obtained was shown in Table 4.5.1 (a). The p-value obtained for this age group (20-29) was 0.903. Significance value that was
Between the 1st and 2nd break point readings the p-value obtained was 0.552, meanwhile the p-value between the 2nd and 3rd break point readings was 0.333. When comparing the 1st and 3rd break point readings the p-value was 0.605. When comparing the break point readings in the Chinese race in the 30-39 age group the p-value obtained was 0.956. For the 1st and 2nd break point readings the p-value obtained was 0.991, meanwhile the p-value between the 2nd and 3rd break point readings was 0.809. The 2nd and 3rd break point readings has a significance value of 0.783. In the Indian race for this age group (30-39), the p-value obtained when comparing the break point readings was 0.981. The 1st and 2nd break point readings shows a significance value of 0.849, while between the 2nd and 3rd break point readings the significance value obtained was 0.947. The 2nd and 3rd break point readings has a significance value of 0.902. Since all the significance values were above 0.05, this shows that there were no significant differences between the three break point readings within the three races in this age group