Non-linear regression is a statistical method used to model relationships between variables when the relationship is not a straight line. Unlike linear regression, which assumes a constant rate of change, non-linear regression can accommodate curves and more complex patterns. This makes it useful for analyzing data in various fields, such as biology, economics, and engineering. In non-linear regression, the model is defined by a non-linear equation, which can take many forms, such as exponential, logarithmic, or polynomial functions. The goal is to find the best-fitting curve that minimizes the difference between observed data points and the predicted values from the model. This approach allows for more accurate predictions in situations where linear assumptions do not hold.