Data fitting is a statistical process used to create a mathematical model that best represents a set of observed data points. This involves selecting a function or equation that can describe the relationship between variables, allowing for predictions and insights based on the data. The goal of data fitting is to minimize the difference between the observed values and the values predicted by the model. Techniques such as linear regression or non-linear regression are commonly used to achieve this, helping researchers and analysts understand trends and patterns within the data.