regression equation : An equation obtained from a regression analysis, expressing the dependent variable as a linear function of the independent variables.

When a regression analysis is used, a regression equation is created. It is also known as a "regression line". This is an equation that allows the calculation of predicted values for the dependent variable.

For example, imagine a criminologist is studying the amount of crime according to various factors such as: number of police in precinct, population density of suburb (measured as "people per square mile"), and average household income (measured in dollars per year). These three variables would be labelled as x1 (number of police), x2 (population density) and x3 (income). crime rate is y.

The regression equation from the study is y = -2.3 * X1 + 7.1* x2 + .03 * x3.

With this equation, you can calculate a y value for any given values of x1, x2, and x3. Note that what you obtain is a prediction for the crime rate y, not the actual crime rate. The estimated accuracy of the prediction is given by r r squared. The numbers that x1 etc are multiplied by are called coefficients of the equation.