Three Dangerous Statistical Mistakes
It’s all too easy to make mistakes involving statistics.
It’s all too easy to make mistakes involving statistics.
Armed with a degree in organizational psychology, I started my career in operational improvement during the early 1970s with a nationally recognized Hartford, Connecticut-based insurance company.
(ASQ: Milwaukee, WI) -- The results of ASQ’s 25th annual Salary Survey show strong average salaries for quality professionals in 2011 and fewer lay-offs as companies continue to see the value of quality and its positive impact on an organization.
Many times measurements are made using measurement increments which are too large for the job. Fortunately this problem is easily detected by ordinary, production-line process behavior charts.
In production plants across the globe, lean manufacturing techniques are being used to meet increasing demands placed on manufacturers.
The teaching of lean concepts is typically tuned to continuous processes: Day in, day out, value flows continuously from suppliers until the final product reaches the customer.
During the first winter storm this year in the Northeast, I found myself, along with hundreds of thousands of folks in the area, without power for the better part of a week. It was a long wait before the lights came on… and the heat.
A short time after I moved into operations as the vice president of manufacturing, our assembly department made an early and, dare I say, imperfect attempt to realign the factory floor for ease-of-material delivery and pick up.
At a recent health-care conference I had a conversation with Mary, a Six Sigma Black Belt for a 700-bed hospital. She told me that the hospital had only a few copies of Minitab software, which was shared by several people.
From the perspective of data analysis, rare events are problematic. Until we have an event, there is nothing to count, and as a result many of our time periods will end up with zero counts.
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