**jm + distributions**
4

Random with care

january 2018 by jm

Some tips about RNGs and their usage

(via Tony Finch)

coding
random
math
rngs
prngs
statistics
distributions
(via Tony Finch)

january 2018 by jm

Good advice on running large-scale database stress tests

december 2014 by jm

I've been bitten by poor key distribution in tests in the past, so this is spot on: 'I'd run it with Zipfian, Pareto, and Dirac delta distributions, and I'd choose read-modify-write transactions.'

And of course, a dataset bigger than all combined RAM.

Also: http://smalldatum.blogspot.ie/2014/04/biebermarks.html -- the "Biebermark", where just a single row out of the entire db is contended on in a read/modify/write transaction: "the inspiration for this is maintaining counts for [highly contended] popular entities like Justin Bieber and One Direction."

biebermark
benchmarks
testing
performance
stress-tests
databases
storage
mongodb
innodb
foundationdb
aphyr
measurement
distributions
keys
zipfian
And of course, a dataset bigger than all combined RAM.

Also: http://smalldatum.blogspot.ie/2014/04/biebermarks.html -- the "Biebermark", where just a single row out of the entire db is contended on in a read/modify/write transaction: "the inspiration for this is maintaining counts for [highly contended] popular entities like Justin Bieber and One Direction."

december 2014 by jm

Nassim Taleb: retire Standard Deviation

january 2014 by jm

Use the mean absolute deviation [...] it corresponds to "real life" much better than the first—and to reality. In fact, whenever people make decisions after being supplied with the standard deviation number, they act as if it were the expected mean deviation.'

Graydon Hoare in turn recommends the median absolute deviation. I prefer percentiles, anyway ;)

statistics
standard-deviation
stddev
maths
nassim-taleb
deviation
volatility
rmse
distributions
Graydon Hoare in turn recommends the median absolute deviation. I prefer percentiles, anyway ;)

january 2014 by jm

Fat Tails

july 2013 by jm

Nice d3.js demo of the fat-tailed distribution:

dataviz
via:hn
statistics
visualization
distributions
fat-tailed
kurtosis
d3.js
javascript
variance
deviation
A fat-tailed distribution looks normal but the parts far away from the average are thicker, meaning a higher chance of huge deviations. [...] Fat tails don't mean more variance; just different variance. For a given variance, a higher chance of extreme deviations implies a lower chance of medium ones.

july 2013 by jm

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