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Bonnie K. Stone

In today’s world, data is everywhere. Many people think data is easy to collect and easy to understand. It is often a challenge to do it right! In my blog posts, my mission is to impart information that will make your data collection and analysis task easier.  
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I started my data analysis career in the Space Shuttle Program, as part of the Trend Analysis and Corrective Action Department at Kennedy Space Center.  My group searched for trends and recurring problems in the vast amounts of data generated at each shuttle launch. Our motto was “turning data into useful information.” Hanging over the entrance to the Johnson Space Center Mission Evaluation Room... Continue Reading
Ahoy, matey! Ye’ve come to the right place to learn about Value Stream Maps (VSM).  Just as a treasure map can lead a band o’ pirates to buried treasures, so too can the VSM lead a process improvement bilge rat to the loot buried deep inside a process! Minitab’s Quality Companion has an easy-to-use VSM tool to guide yer way. Use a value stream map to illustrate the flow of materials... Continue Reading

7 Deadly Statistical Sins Even the Experts Make

Do you know how to avoid them?

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For all you creative and fun-loving folks out there, in this blog post I'm going to share a puzzle instead of a story or lesson. The holiday season is getting into full swing here in the United States, and that gives us an opportunity to pause and reflect, and even have a little fun while still thinking about how we can improve our processes and products.   Perhaps you're wondering what a puzzle... Continue Reading
In Parts 1 and 2 of this blog series, I wrote about how statistical inference uses data from a sample of individuals to reach conclusions about the whole population. That’s a very powerful tool, but you must check your assumptions when you make statistical inferences. Violating any of these assumptions can result in false positives or false negatives, thus invalidating your results.  The common... Continue Reading
In Part 1 of this blog series, I wrote about how statistical inference uses data from a sample of individuals to reach conclusions about the whole population. That’s a very powerful tool, but you must check your assumptions when you make statistical inferences. Violating any of these assumptions can result in false positives or false negatives, thus invalidating your results.  The common data... Continue Reading
Statistical inference uses data from a sample of individuals to reach conclusions about the whole population. It’s a very powerful tool. But as the saying goes, “With great power comes great responsibility!” When attempting to make inferences from sample data, you must check your assumptions. Violating any of these assumptions can result in false positives or false negatives, thus invalidating... Continue Reading