Having a normally shaped histogram is not a prerequisite for placing your data on a process behavior chart. Neither is it inevitable that a predictable process will display a mound shaped histogram.
This book provides the first careful and complete examination of the relationship between the normal distribution and the process behavior chart. It clears up much of the confusion surrounding this subject, and it can help you overcome the superstitions that have hampered the effective use of process behavior charts.
Topics include:
the history of the normal distribution and early attempts to use it to analyze data
the shortcomings of goodness-of-fit tests
how to really compute parts-per-million defect rates
the fundamental difference between theory and practice
the relationship between R&D and SPC
the linkage between the normal distribution and basic constants in chart formulas
how non-normal distributions affect these basic constants
how three-sigma limits work with over 1100 different probability models
the shortcomings of average run lengths as a tool for sensitivity analysis