Why bother to plot your data? A simple shortcut is available that will allow you to do your analysis without the data getting in the way. How do you accomplish this breakthrough? Read on.
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This marvelous advance in analysis is known as the “data-free graph.” As usual we begin with a collection of data as in figure 1.
Figure 1:
Now this is way too much detail. We cannot readily absorb this much information, so we simply extract a few summary statistics from our data. First on this list might be the average or a median. A median value for the number of blemishes per roll is 28.5.
Next we need to characterize how the data are spread out above and below the median, so we find the minimum and maximum values for the data. For the number of blemishes per roll these values are 21 and 38 respectively. To further refine our summary of how the data spread out we also find the quartiles for the data. The quartiles for the number of blemishes per roll are 23 and 35.
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Comments
Figure 8 shows excellently
Data Free?
You sly fox, you. You had me fooled. As I'm reading the article with great eagerness, as i always do your pieces, I'm thinking to myself "What are these words coming out of Don Wheeler's mouth? Has he had a nervous breakdown or what?" Silly me to forget what day it was. Great satire, Don, and I was your April Fool. (Oh well, I've been a fool before and I daresay i will be again.)
For Bill
Distribution Transform
Dr. Wheeler,
I'm disappointed that you failed to properly transform the data to the correct distribution in each case. This would have solved the histogram problem without having to dig into the process that produced the data. Do you really expect me to leave my desk and talk to those production people? My software applies the transformation so easily - it even suggests which distribution to use! I'll leave the messy details to the production folks.
Happy April Fools. - Great article.
Not me
You didn't fool me. I have too many of your books on my shelf!!
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