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poissonisfish.com
| | hbiostat.org
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| | sportscidata.com
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| | Recently Dan Weaving and the research group at Leeds Beckett University put out a paper outlining how to perform a type of dimension reduction on training load data: principal component analysis (PCA). The benefit of such an analysis is it can reduce a large number of metrics into a more manageable dataset. This may uncover...
| | algobeans.com
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| | You are exploring the nutritional content of food. How can food items be differentiated? How might they be classified? PCA derives underlying variables that help you slice your data for these insights.
| | kieranhealy.org
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| With the 2020 U.S. Census in motion already, I've been looking at various pieces of data from the Census Bureau. I decided I wanted to draw some population pyramids for the U.S. over as long a time series as I could. What's needed for that are tables for, say, as many years as possible that show the number of males and females alive at every year of age from zero to the highest age you're willing to track. This sort of data is available on the Census website. But it tuned out to be somewhat tedious to assemble into a single usable series. (Perhaps it's available in an easy-to-digest form elsewhere, but I couldn't find it.) I initially worked with a couple of the excellent R packages that talk to the Census API (tidycensus and censusapi), hoping they'd give m...