What is non-linear regression and how is it used?

What is non-linear regression and how is it different from linear regression?

Non-linear regression is a form of regression analysis where the relationship between variables is modeled as a non-linear function. Unlike linear regression, which assumes a straight-line relationship, non-linear regression can fit curves to data.

Can you give me an example of a non-linear regression model?

Sure! A common example is the logistic regression model, which is used for binary outcomes. It models the probability of an event occurring as a function of one or more predictor variables.

What are some applications of non-linear regression?

Non-linear regression is widely used in fields like biology for growth modeling, economics for demand forecasting, and engineering for system modeling.

How do I choose the right non-linear model for my data?

Choosing the right model involves understanding the underlying relationship in your data, visualizing it, and testing different models to see which one fits best based on criteria like R-squared or AIC.