Data fitting is the process of building a curve or a mathematical function that has the best match with a set of previously collected points. Curve fitting can relate to both interpolations, where exact data points are required, or smoothing, where a flat function that approximates the data is built. We are talking about curves fitting in a regression analysis, which is most concerned with statistical inference problems, as well as the uncertainty that a curve coincides with observed data that has random errors. The approximate curves obtained from the data fitting can be used to help display data, to predict the values of a function where no data is available, and to summarize the relationship between two or more variables.

Figure 7.18: Linear interpolation of collected data
We have seen some examples of curve fitting in the regression chapter. On that occasion, we could see that the mathematical formulas that allow us to predict the trend of a particular...