The article introduces a simple method to test if a statistical model accurately represents real-world data. By using specific calculations on the model's errors, researchers can determine if the model is a good fit. The tests are reliable and powerful when the right calculations are used. Different ways of calculating these tests are discussed, and their performance is evaluated through computer simulations. The method is then applied to analyze gasoline demand models, showing its practical use in real-world scenarios.