Regression
Regression is a statistical measure, calculated in order to compare one dependant variable with one or many other independent, explanatory, variables, where dependent variable is denoted with the "Y" sign.
Two types of regression analysis are used: linear regression and multiple regression analysis.
Linear regression is calculated as follows: Y = a + b*X + u, where Y is the dependant variable, "a" is the value of Y when X equals zero (called intercept), X is the explanatory and independent variable, "b" is the slope of the line and "u" is the regression residual.
As seen, linear regression uses only one independent variable to predict the independent one.
Multiple regression is calculated as follows: Y = a + b1*X1 + b2*X2 + ... + bp*Xp, where "a" is the intercept, "b" is the slope of the line and X is the independent variable. As seen, multiple regression analysis uses more independent variables in order to determine the relation between them and the Y.
| Related Terms: Kappa |