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A few years ago, I went to visit my sister on the Caribbean island of Grenada and she took me to the local market to buy some hot sauce. As we were walking around, she told me about a young boy at the market who was legendary for selling more than any of the other boys. “How?” I asked. It turned out he always carried a notebook with him. Every day, he would systematically vary his clothes, what he said when he approached potential buyers, how much he would laugh, if he would dance, and many more variables.
Many of us believe in a rational world. “If he really cared,” we say, “he’d be doing well at his job.” Now, sometimes that’s true.
This is part 4/4 highlighting some of the Best Of material on IWT. I’ve written IWT for nearly 8 years, starting back when I was a cocky college kid. Not a lot has changed since then. The sad part about writing a blog, besides the fact that my readership is overwhelmingly slightly socially awkward dudes, is that lots of great, popular posts get buried in the archives. So I decided to collect some of my most visited posts, especially for new readers who aren’t familiar with a lot of the ground I covered in 2010 and 2011. Ok, here you go.
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For the uncertainty to be truly meaningful, it must address the entire measuring process, which may have uncertainties associated with factors such as equipment calibration, operator skill, sample variation, and environmental factors. When a measurement has more than one identifiable source of measurement uncertainty, then the combined standard uncertainty (u c ) must be calculated. Calculating the combined standard uncertainty is a two step process.
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