Curve Fitting

Curve fitting is the process of finding a mathematical function that best describes the relationship between a set of data points. Given scattered or noisy measurements, the goal is to choose a model, such as a line, polynomial, exponential, or more complex function, and adjust its parameters so the resulting curve matches the data as closely as possible. This is usually done by minimizing some measure of error.

Curve fitting is widely used as a core part in science, engineering, economics, and statistics to model trends, make predictions, smooth out noisy data, or extract meaningful parameters (like growth rates or decay constants) from experimental results. While curve fitting is most often introduced using two-dimensional data (x and y coordinates), the same underlying principles extend naturally to three-dimensional points, and even higher dimensions.