This is a computational tool used to assess how well a statistical model describes a set of observations. Functionally, it provides a quantitative measure indicating the concordance between predicted values from the model and the observed values in the dataset. For instance, if one attempts to fit a normal distribution to observed test scores, this tool will quantify how well the theoretical normal curve aligns with the actual distribution of scores.
The importance of these tools lies in their ability to validate statistical models. By providing a numerical evaluation of the model’s performance, it enables researchers and analysts to determine whether the model is a reliable representation of the underlying process. Historically, these calculations were performed manually, often involving cumbersome formulas and tables. The advent of computational tools has significantly streamlined this process, enabling faster and more accurate assessments, thereby allowing for more rigorous model selection and refinement.
