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of data from benchmarks etc. Implements "Student's t" for various confidence levels, defaults to 95%. If your benchmarks are not significant at the 95% confidence level, we don't want to hear about it.
51 lines
2.0 KiB
Plaintext
51 lines
2.0 KiB
Plaintext
$FreeBSD$
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A small tool to do the statistics legwork on benchmarks etc.
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Prepare your data into two files, one number per line
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run
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./ministat data_before data_after
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and see what it says.
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You need at least three data points in each data set, but the more
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you have the better your result generally gets.
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Here are two typical outputs:
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x _1
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+ _2
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+--------------------------------------------------------------------------+
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|x + x+ x x x + ++ |
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| |_________|______AM_______________|__A___________M_______________||
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+--------------------------------------------------------------------------+
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N Min Max Median Avg Stddev
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x 5 36060 36138 36107 36105.6 31.165686
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+ 5 36084 36187 36163 36142.6 49.952978
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No difference proven at 95.0% confidence
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Here nothing can be concluded from the numbers. It _may_ be possible to
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prove something if many more measurements are made, but with only five
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measurements, nothing is proven.
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x _1
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+ _2
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+--------------------------------------------------------------------------+
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| + |
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| x + +|
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|x x x x + +|
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| |_______________A_____M_________| |_M___A____| |
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+--------------------------------------------------------------------------+
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N Min Max Median Avg Stddev
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x 5 0.133 0.137 0.136 0.1354 0.0015165751
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+ 5 0.139 0.14 0.139 0.1394 0.00054772256
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Difference at 95.0% confidence
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0.004 +/- 0.00166288
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2.95421% +/- 1.22812%
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(Student's t, pooled s = 0.00114018)
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Here we have a clearcut difference, not very big, but clear and unambiguous.
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