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At this point, I hope you are already familiar with simple linear regression. In many cases, however, you may face problem that your data is not linear but have tendency to make a curve. Non-linear regression is a functional relationship that does not produce a straight-line in the scattered plot. Some non-linear curves can be transformed into linear regression. In this simple tutorial, you will learn how to transform some non-linear regression into linear regression.

Here is step by step on when and how to use curvilinear or non-linear regression:

- Firstly, you plot your data into scattered plot (XY type graph)
- Examine if there is any non linear relationship on the scattered plot
- Guess the model that relate X and Y and transform the model into linear model
- Compute the parameters and statistical fitness of the model
- Transform back the parameter to non linear model.

**Topics**

Scattered Plot

Non-Linear Regression

Non-Linear Transformation

Power Curve

Logarithmic Curve

Square Root Curve

**See Also**: Regression tutorial, Power Rules, Logarithm Rules, Kernel Regression

**Preferable reference for this tutorial is**

Teknomo, Kardi. Non-Linear Transformation for Regression. http:\\people.revoledu.com\kardi\ tutorial\Regression\NonLinear\