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%.