Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

Multiple regression equations designed to explain or predict should be validated. This tutorial shows how recalculation of the coefficient of determination on hold-out sample data or new sample data ...

Learn to apply multiple regression techniques to predict continuous outcomes, use logistic regression for binary outcomes, and employ Cox regression for survival analysis.

In the past, it was necessary to create an equation to make forecasts from regression analysis. Seldom were these equations easy to calculate or as simple as x=y2.

Regression analysis (or, more specifically, linear regression analysis) finds a "line of best fit" between a response variable and one or more explanatory variables. This applet allows users to look ...

Learn how to graph linear regression in Excel. Use these steps to analyze the linear relationship between an independent and a dependent variable.

Interpreting logistic regression analysis In a logistic regression model, the coefficients (represented by β in the equation) represent the log odds of the outcome variable being 1 for each one-unit ...

Using historical data and regression analysis has its limitations in business forecasting. For example, a significant correlation between the independent and dependent variable does not ...

By contrast, nonlinear regression analysis or nonlinear least-squares fitting (NLSF) refers to equations that are nonlinear in their parameters.