A statistical procedure using a body of measurable independent variables to compute an
equation that successfully measures and forecasts the variance in another variable, the dependent
variable. Regression analysis multiplies each of the independent variables by a beta coefficient and
adds the results together. The beta coefficients of the independent variables are one of the most
important parts of the set of results produced by regression analysis. More important, explanatory
variables have higher beta values. The large the sample size, the greater the statistical
significance of the results. The total amount of variation in the dependent variable is measured by
the coefficient from 0% to 100%.