The origin of the common Six Sigma "long term" expression is explained in detail below.  It came from that farcical "long term drift/shift" of +/-1.5 sigma that forms the "six sigma" of Six Sigma.   The clear advice is stick to Shewhart Charts.http://www.qualitydigest.com/inside/six-sigma-article/sick-sigma.html"

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The +/-1.5 shift was introduced by Mikel Harry. Where did he get it? Harry refers to a paper written in 1975 by Evans, “Statistical Tolerancing: The State of the Art. Part 3. Shifts and Drifts.” The paper is about tolerancing. That’s how the overall error in an assembly is affected by the errors in components. Evans refers to a paper by Bender in 1962, “Benderizing Tolerances—A Simple Practical Probability Method for Handling Tolerances for Limit Stack Ups.” He looked at the classical situation with a stack of disks and how the overall error in the size of the stack related to errors in the individual disks. Based on probability, approximations and experience, he asks:

"How is this related to monitoring the myriad processes that people are concerned about?" Very little. Harry then takes things a step further. Imagine a process where five samples are taken every half hour and plotted on a control chart. Harry considered the “instantaneous” initial five samples as being “short term” (Harry’s n=5) and the samples throughout the day as being “long term” (Harry’s g=50 points). Because of random variation in the first five points, the mean of the initial sample is different from the overall mean. Harry derived a relationship between the short-term and long-term capability, using the equation to produce a capability shift or “Z shift” of 1.5. Over time, the original meaning of instantaneous “short term” and the 50-sample point “long term” has been changed to result in long-term drifting means.

Harry has clung tenaciously to the “1.5,” but over the years its derivation has been modified. In a recent note, Harry writes, “We employed the value of 1.5 since no other empirical information was available at the time of reporting.” In other words, 1.5 has now become an empirical rather than theoretical value. A further softening from Harry: “… the 1.5 constant would not be needed as an approximation.”

Good evening everyone!

It may be a silly question but i wanted to ask if there is any chance that the short term variation can be larger than the long term variation! Thanks in advance!!