Seen & Heard
William Hooper’s article, "Probing Probabilities" (March 2014, pp.18-22), provides an excellent review of Bayes’ theorem and its implications for conditional probabilities.But if his results "defy instinct," as the issue’s cover proclaims, it might be because our instinct has been undermined by the sophistication of our knowledge.
The article opens with a medical question asking what the likelihood is that a person who tests positive for a disease that occurs in only 1% of the population actually has the disease, assuming the test is 95% accurate. The author explains Bayes’ theorem and works through the math to determine the probability is only 16%—not 80% or 95%, as most Harvard Medical School doctors apparently responded. But the answer could have been arrived at much more simply.
Consider a representative group of 100 people, one of whom has the disease and 99 who do not. The test, being 95% accurate, will almost certainly yield a positive result for the person with the disease. In addition, it can be expected to generate about five false positives from the 99 healthy people in the sample. So, in six positive results, only one is accurate. The likelihood of a person with a positive test actually having the disease would be one in six, or 16.7%, a result that differs only slightly from the exact answer of 16.2% obtained from Bayes’ theorem.
There is certainly a time for precision. But if our intent is to help doctors with no knowledge of statistics understand why the answer is not 80% or 95%, or to reassure a patient who has just obtained a positive test result, the simple example above may be far more effective than trying to teach them Bayes’ theorem. The same might be true for trying to explain the likelihood of defective parts to a manager.
In full disclosure, I cannot take credit for the simple analysis above; that credit belongs to my wife, a nurse. As I was working through Bayes’ formula and searching for my calculator, I asked her the question and she immediately identified the correct answer using the logic above. Sometimes simpler really is better.
In response to "Will to Live" (March 2014, pp. 32-37), This is an impressive story. My quality manager experienced something similar. He was diagnosed with pulmonary fibrosis and was lucky to get a lung transplant. By that time, he could not walk and was lacking oxygen. When I went to visit him one week after the operation, I was amazed with his breathing, which was easy and normal. He reacted to the situation like a quality professional—he told me that the quality is not an accident, it’s a result of intelligent work. That famous quality quote could not be used in a better circumstance.
The "Learning From Experience" (February 2014, pp. 14-19) interviews with lean experts are inspiring. The common theme from all interviewees is that lean should be viewed as a "common sense revolution" in recognizing that people learn by doing. Only people who are capable, motivated and aligned in the gemba of an organization can make a difference—not opportunistic lean consultants only motivated by exploiting this movement to ensure they have a steady stream of customers.
The latest ASQ TV episode focuses on lean and Six Sigma. In the episode:
- Learn the difference between lean and Six Sigma methods.
- Hear how a global financial firm improved response times and increased revenue.
- Examine waste analysis.
Watch for a new episode available May 13 discussing the global impact of quality. Visit http://videos.asq.org to access the full video library.
- Tune in for more
Available in mid-May, watch a video of Shu Liu, author of this month’s cover story, "Catching Fire" (pp. 18-24), as he talks more about the seven strategies to fuel your team’s creativity.
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