Nonparametric methods in scientific research offer flexibility and reliability without strict assumptions. These methods are useful for studies with small sample sizes or qualitative data. Part 2 of the article focuses on nonparametric goodness-of-fit tests like Pearson’s and Kolmogorov tests, as well as tests for homogeneity like chi-squared and Kolmogorov-Smirnov tests. These tests compare empirical and theoretical distributions to detect differences. Kolmogorov test is more sensitive than Pearson’s chi-squared test in capturing subtle nuances. The article provides examples and step-by-step instructions for applying these tests, giving researchers a practical tool for statistical analysis.