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S Apr 8, 2013 at 15:19 history bounty ended chmullig
S Apr 8, 2013 at 15:19 history notice removed chmullig
Apr 3, 2013 at 1:11 comment added Cam.Davidson.Pilon I'm too lazy to write something up, but this is probably a practical solution using ABC algorithms.
Apr 3, 2013 at 0:05 answer added Jamie Hall timeline score: 2
Apr 1, 2013 at 12:28 answer added waferthin timeline score: 2
Apr 1, 2013 at 5:26 answer added guest47 timeline score: 2
Apr 1, 2013 at 1:53 history tweeted twitter.com/#!/StackStats/status/318541652962734081
S Apr 1, 2013 at 0:19 history bounty started chmullig
S Apr 1, 2013 at 0:19 history notice added chmullig Draw attention
Mar 30, 2013 at 0:51 comment added chmullig I know it's roughly normal, and it's bounded between [50, 160].
Mar 30, 2013 at 0:28 comment added Glen_b There are an infinite number of distributions which could reasonably produce these sample characteristics. Are your values limited or - at least effectively - unbounded; or perhaps bounded at one end)? Have you considered trying say a gamma distribution (possibly with a shift-parameter), which would let you fit that mild skewness?
Mar 29, 2013 at 23:50 comment added gung - Reinstate Monica This is not quite the same thing, but might be interesting anyway: Chatterjee & Firat (2012). Generating Data with Identical Statistics but Dissimilar Graphics.
Mar 29, 2013 at 22:59 history edited chmullig CC BY-SA 3.0
added 38 characters in body
Mar 29, 2013 at 22:59 comment added chmullig Yes, I have n. And yes, Xs is standard deviation. Updated!
Mar 29, 2013 at 22:55 review First posts
Mar 29, 2013 at 23:26
Mar 29, 2013 at 22:54 comment added whuber The min and max will be more useful if you have the count of your data as well. Is that available? Is Xs the sample standard deviation?
Mar 29, 2013 at 22:37 history asked chmullig CC BY-SA 3.0