Six Sigma
Read this chapter, which gives a clear description of Six Sigma, when it is used, and how to interpret the results.
Statistics and Six Sigma
Analysis Methods
Two ways to analyze data for similarities (percent confidence) would be running a regression analysis or an analysis of variance (ANOVA). The difference between these two methods of analysis is that the ANOVA is for comparing independent groups such as 4 different reactor compositions that are supposed to make the same product (in reality this doesn't happen). A linear regression would be used for data that is dependent on each other, such as looking at the difference between slurry product permeabilities when a one-reactant composition in the process is changed. The percent confidence is the same as the student's t-test, where you would want a t value (error) that is less than 0.05 to have statistically similar data.
One statistical program that is widely used in Six Sigma projects is MINITAB. MINITAB is similar to Microsoft Excel but has much greater statistical analysis capabilities. This program allows you to run linear regressions and ANOVAs by the click of an option. It also graphs not only in 2-D but 3-D as well and runs statistical analysis methods that are more in depth than those offered in Excel. MINITAB graphical and analytical tools can provide insight and information throughout the DMAIC process. MINITAB can be used to:
- Identify - visualize sources of variation and relationships among variables
- Verify - having statistical confidence behind conclusions