Statistics and Reality – Part 1
Abstract: Common uses on “organizational data” such as variance tables, trends analysis, rankings, stretch goals, and tougher standards can actually sabotage improvement if carried out without a clear purpose in mind. The key to success is to ask better questions and understand the context of the processes in order to respond to variation appropriately and improve quality. In particular, process inputs fall into the six categories of “people”, “methods”, “machines”, “materials”, “measurements (data)”, and “environment”, each of which is a potential source of variation. There is a distinction between enumerative statistics and analytic statistics. The latter is a predictive way of thinking that is fundamental to quality improvement. Analytic studies have the complexity of trying to predict a process that will take place in the future. This prediction cannot rely on the result of any one experiment; the experiment must be repeated under as many different circumstances as can be foreseen to represent the circumstances surrounding the process in the future. Most of the time, this creates uncertainty that is unknown and unknowable. Statistics is “the art and science of collecting and analyzing data”, with emphasis given on the collection portion.
Keywords: Statistical thinking - Process-oriented thinking - Data acquisition