In this section you can make use of some regression or data fitting tools online.

Regression tools allow fitting a function to a set of data points by finding the parameters that best approximate it. My interest in regression comes from my believing that nonlinear regression and some other algorithms can form the basis of an automated scientific research program that given any set of experimental data will be able to automatically find the underlying patterns and laws, which would be very valuable for any scientific purpose.

Indeed, today's data fitting, data modeling or approximation methods do this task to a certain level by making use of nonlinear regression with lists of functions, in a similar way to the tool shown in the last page of this section, but these methods can be taken a step further to build real automated scientific research programs.

• Linear Regression (LR)
• Logarithmic Regression (LnR)
• Exponential Regression (ExpR)
• Power Regression (PowR)
• Polynomial Regression (PR)
• Multiple Linear Regression (MLR)
• Multiple Polynomial Regression (MPR)
• Nonlinear Regression (NLR)