The article investigates different statistical tests used to check if the variance of residuals in a linear regression model is consistent. The researchers compared nine tests using simulations and found that the Glejser and Park tests are best for detecting heteroscedasticity in certain scenarios, while the White and Harrison-McCabe tests are best for detecting homoscedasticity in others, especially for small sample sizes. They injected different types of variance patterns into the models and evaluated the tests' performances using statistical analysis software.