The watching statistics are needed mostly in industry for production processes that sometimes stray from proper adjustment. These statistics monitor variation, and their job is to distinguish the usual random variation (called common causes) from abnormal changes (called special causes).

These statistics are usually from a time series, and the patterns they exhibit over time are clues to what is happening to the production process. If they are to be useful, the data for these statistics need to be collected and analyzed promptly so that any problems they detect can be fixed.

The use of SQC techniques became popular in the 1980s as industry began to better understand the issues of quality, after the pioneering effort of Japanese industry and under the leadership of W. Edwards Deming and Joseph Juran.

This whole area of statistics is called Statistical Process Control (SPC) or Statistical Quality Control (SQC). The most basic tool is a graph called a control chart (or Shewhart control chart, named for the inventor, Walter Shewhart). In some industries, SQC techniques are taught to everyone—engineers, mechanics, shop floor operators, even managers.

In addition to control charts, JMP offers many quality and process tools, such Pareto charts, measurement systems analysis, capability analysis, and cause and effect diagrams (also known as fishbone charts or Ishikawa diagrams).

This chapter provides an overview of control charts and process capability studies.