ABSTRACT
Regression and correlation are two important mathematical associations used in statistics. Correlation analysis is concerned with the extent to which the variables are related, that is, the strength of the relationship. Regression and correlation analyses can only show how, or to what extent variables are associated with each other. The overall quality of the regression line is reflected by the standard error of the estimate. The least squares method provides an estimated regression equation that minimizes the sum of squared deviations between the observed values of the dependent variable and the estimated values of the dependent variable. In developing the least squares estimated regression equation and computing the coefficient of determination, no probabilistic assumptions or statistical inferences have been made. An important idea that must be understood before we consider testing for significance in regression analysis involves the distinction between a deterministic analysis and a probabilistic analysis.
