Understanding Normality Tests: A Guide to the Kolmogorov-Smirnov Test **
Introduction: This article explains the Kolmogorov-Smirnov test, a statistical tool used to determine if data follows a normal distribution. Sections: ① The Kolmogorov-Smirnov Test: This section defines the test and its purpose, explaining how it compares observed data to a theoretical normal distribution. ② Interpreting the Results: This section clarifies the significance level (p-value) and its role in determining normality. It explains the decision rule based on the p-value. ③ Example Application: This section uses the provided data (X1, X2, and Y) to demonstrate how to interpret the test results. It explains the conclusions drawn based on the p-values. Conclusion:** This section summarizes the importance of normality testing in statistical analysis and emphasizes the role of the Kolmogorov-Smirnov test in determining data distribution.