This site provides free online tools for mathematical regression analysis. Regression analysis is a statistical method used to examine the relationship between a dependent variable and one or more independent variables.
Our tools allow you to:
Choose a regression type from the options below to get started.
Find the best-fitting straight line through a set of points.
Predict binary outcomes and calculate probabilities.
Fit a polynomial equation to your data points.
Linear regression with L2 regularization to prevent overfitting.
Linear regression with L1 regularization for feature selection.
Combines L1 and L2 penalties of Lasso and Ridge for better variable selection.
Uses support vectors to create a regression model with a margin of tolerance.
Creates a tree-like model to predict values based on decision rules.
Ensemble method that builds multiple decision trees for better predictions.
Builds models sequentially to correct errors of previous models.
Estimates conditional quantiles of the response variable distribution.
Uses Bayesian methods to provide full probability distributions for parameters.
Reduces dimensionality using PCA before performing regression.
Finds components that maximize covariance between predictors and response.
Analyzes and forecasts time-dependent data using ARIMA/SARIMA models.