The article compares different tests for checking if data follows a normal distribution. They used a new algorithm to compare these tests and found that some tests are more powerful than others. As the sample size increases, the power of the tests also increases. The Shapiro Wilk, Shapiro Francia, and Anderson Darling tests are the most powerful, while the Jarque Bera test is less powerful. The Lilliefors test has better power than the Jarque Bera test. The Cramer-Von-Mises test performs better than the Pearson chi-square test. Randomness of generated numbers was also tested using different tests.