K-S — Valor Crítico
- Created by
- Renato Passos, Eng. de Software
- Reviewed by
- Renato Passos, Eng. de Software
Last updated: Apr 18, 2026
Formula
K-S
About this calculator
The K-S is a calculator that helps to determine the critical value of a statistical test. This tool uses the Kolmogorov-Smirnov formula to calculate the critical value based on the sample data and the desired significance level.
The critical value is essential in statistical testing, as it indicates the probability of rejecting the null hypothesis in favor of the alternative hypothesis. With this calculator, you can get the critical value quickly and accurately.
Remember to use this calculator when performing statistical tests to compare the distribution of a variable across a sample. Additionally, consider common pitfalls, such as choosing the significance level and interpreting the results.
When using this calculator, it's essential to understand that the critical value is only a measure and not enough to make definitive decisions. It's crucial to consider other factors and evaluate the results critically.
Frequently asked questions
What is the standard significance level used by the K-S?
The standard significance level used by the K-S is α = 0.05. However, you can adjust the significance level according to the specific needs of your test.
How do I choose the sample size (n) for my test?
The sample size (n) should be determined based on the number of observations needed to obtain statistically significant results. In general, a larger sample size is recommended for more rigorous tests.
What is the probability distribution used by the K-S?
The K-S uses the Kolmogorov-Smirnov probability distribution, which is a continuous distribution used to test the null hypothesis that a variable follows a specific distribution.
How do I interpret the critical value calculated by the K-S?
The critical value calculated by the K-S should be interpreted in conjunction with the results of your test. If the value obtained is less than the critical value, you may reject the null hypothesis in favor of the alternative hypothesis.