Statistical Tools for Building Process Performance Baselines (PPBs) and Models (PPMs) for Level 5

Here are some commonly used statistical tools for  building Process Performance Baselines (PPBs) and Models (PPMs) for CMMI Level 5:

For Sub Group Identification

• F-test for equality of variances (sigma square)
• ANOVA for equality of means (mu)
• Additionally Tukey's test can be applied to group the subgroups in case difference in means come out as significant from ANOVA

Process Performance Baselines (PPBs)

•  X MR Control Charts

Process Performance Models (PPMs)

• Multiple Linear Regression
• Following model adequacy tests also need to be performed
• Normality of residuals or errors using Normal Probability Plot
• p-value of Normality check for Y, Xs and residuals (more than 0.05 is desirable - this follows from the fact that null hypothesis in this case is that data follows normal distribution hence null hypothesis being accepted means distribution is normal)
• R square adjusted (more than 70% to 80% is desirable)
• VIF for multi-collinearity or dependency amongst the Xs (less than 10 is desirable)
• p value of the regression coefficients of Xs (less than 0.05 is desirable)
• p value of the regression equation (less than 0.05 is desirable)
• Additionally following can be applied
• Lack-of-fit test
• Variable transformation for satisfying Normality assumption (if nothing works Box Cox Transformation can be tried)