I am watching some old videos of chalkdust on statistics. In one of the videos, the professor calculates quartiles as follows:
But the r.quantile function gives completely different result:
sage:
sage: r.quantile([89, 90, 86, 96, 84, 100, 85, 96, 88, 89])
0% 25% 50% 75% 100%
84.0 86.5 89.0 94.5 100.0
sage:Why is that?
According to the documentation of quantile it takes an optional argument named type which is an integer from 1 to 9. These correspond to different algorithms for calculating quantiles; the default is algorithm 7. You will have to find out which one corresponds to the lecture; my guess is type 5.
sage: r.quantile([89, 90, 86, 96, 84, 100, 85, 96, 88, 89], type=5)
0% 25% 50% 75% 100%
84 86 89 96 100Thanks type=5 did it.
Have a serious look at the section Type of r.help("quantile"). Quantile estimation from a sample is non a trivialproblem, and has caused ink overflows by the barrel...
Asked: 5 years ago
Seen: 429 times
Last updated: Feb 19 '20
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