Regression techniques provide the cost analyst with a valuable analytical tool. This paper describes means of expanding the utility of regression analysis applications in this area. Part I of the paper presented basic definitions and developed measures to assess the accuracy and sensitivity of a regression formula. In particular, it was shown that the Association index, rather than the more commonly used R1, is the pertinent measure of formula sensitivity. We also described several other aspects of evaluating formula reliability—the confidence level, variability in the data, parameter stability, autocorrelation—and discussed indexes especially developed to quantify these factors.