really add tests
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-- http://mathworld.wolfram.com/UniformDistribution.html
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With dist As (
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SELECT random() As val
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SELECT random()::numeric As val
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FROM generate_series(1,5000000) t
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),
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m As (
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SELECT avg(val) mn, count(*) cnt, stddev(val) s
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FROM dist
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)
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)
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SELECT
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abs(sum(power(mn - val,4)) / ( cnt * power(s,4)) - 3 + 1.20) < 1e-3 As kurtosis,
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abs(sum(power(mn - val,3)) / ( cnt * power(s,3))) < 1e-3 As skewness
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FROM dist, m
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GROUP BY m.cnt, m.mn, m.s
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-- does random dist values match within 1% of known values
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abs(CDB_Kurtosis(array_agg(val)) + 1.20) < 1e-2 As kurtosis,
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abs(CDB_Skewness(array_agg(val)) - 0) < 1e-2 As skewness
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FROM dist
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