From mboxrd@z Thu Jan 1 00:00:00 1970 X-Spam-Checker-Version: SpamAssassin 3.4.4 (2020-01-24) on polar.synack.me X-Spam-Level: X-Spam-Status: No, score=-1.9 required=5.0 tests=BAYES_00 autolearn=ham autolearn_force=no version=3.4.4 X-Google-Thread: 103376,df84b868ad64e4f7 X-Google-Attributes: gid103376,public X-Google-Language: ENGLISH,ASCII-7-bit Path: g2news1.google.com!news4.google.com!news.glorb.com!news-in.ntli.net!newsrout1-win.ntli.net!ntli.net!newspeer1-win.ntli.net!newsfe4-win.ntli.net.POSTED!53ab2750!not-for-mail From: "Dr. Adrian Wrigley" Subject: Re: OT: definition of "significant figures" User-Agent: Pan/0.14.2 (This is not a psychotic episode. It's a cleansing moment of clarity.) Message-Id: Newsgroups: comp.lang.ada References: MIME-Version: 1.0 Content-Type: text/plain; charset=ISO-8859-1 Content-Transfer-Encoding: 8bit Date: Sat, 30 Jul 2005 23:44:12 GMT NNTP-Posting-Host: 80.4.127.115 X-Complaints-To: http://www.ntlworld.com/netreport X-Trace: newsfe4-win.ntli.net 1122767052 80.4.127.115 (Sun, 31 Jul 2005 00:44:12 BST) NNTP-Posting-Date: Sun, 31 Jul 2005 00:44:12 BST Organization: ntl Cablemodem News Service Xref: g2news1.google.com comp.lang.ada:3862 Date: 2005-07-30T23:44:12+00:00 List-Id: On Fri, 29 Jul 2005 16:46:36 +0200, Jacob Sparre Andersen wrote: > tmoran@acm.org writes: > >> Given a set of measurements x(i), I'd like to print their average to >> the "correct" number of significant figures. eg >> 1.11, 1.12, 1.08 => "1.1", 1.11, 1.25, 1.35 => "1" >> I've got some adhocery that more or less does it, but is there a >> moderately standard, formal, definition? > > The base 10 logarithm of the standard-deviation of your measurements. this looks like one of those physicist's sign errors! How about: *Minus* the base 10 logarithms of the standard deviation => *decimal places* For example: SD=0.1 => use 1 decimal place SD=0.001 => use 3 decimal places Note that decimal places are not significant figures! Significant figures = Log10 (mean / standard deviation) + C I think people also add in the (small) constant, for good measure, depending on how they feel about the data distribution. YMMV -- Adrian