st: Fwd: Dangers of using MS Excel for statistical work [SEC=UNCLASSIFIED]

[Stas Kolenikov <skolenik@gmail.com>]

Thought this would be useful to know. Background: NIST (National
Institute of Standards) provides a suite of tests
(http://www.nist.gov/itl/sed/gsg/strd.cfm) that push the limits of
computational accuracy in routine statistical computation, e.g.,
having a regression model with a poorly conditioned matrix, or a
nonlinear regression problem with a sharp long ridge near the maximum
of the objective function that a poorly calibrated optimization
algorithm may miss. More serious software packages use these data sets
to gauge how they are doing against them
(http://www.stata.com/support/cert/nist/)... but Excel developers seem
to be oblivious to these standards.

-- Stas Kolenikov, PhD, PStat (SSC)
-- Senior Survey Statistician, Abt SRBI
-- Opinions stated in this email are mine only, and do not reflect the
position of my employer
-- http://stas.kolenikov.name




---------- Forwarded message ----------
From: Geoffrey Brent <geoffrey.brent@abs.gov.au>
Date: Fri, Apr 12, 2013 at 1:18 AM
Subject: Dangers of using MS Excel for statistical work  [SEC=UNCLASSIFIED]
To: anzstat@lists.uq.edu.au


Apologies if this has been circulated already and I missed it, but I
found this article about serious weaknesses in Excel's statistical
functionality rather alarming. This looks to go well beyond "rare bug"
type issues: for instance, when given 27 NIST standard test problems
on nonlinear least squares, it gave badly wrong answers for 11 (but
still claimed to have converged to a correct solution).

http://www.pages.drexel.edu/~bdm25/excel2007.pdf

The article is based on Excel 2007, but it mentions that some of those
problems had been identified > 15 years earlier and remained unfixed.

Geoffrey Brent

Senior Research Officer

Business Survey Methodology  |  Statistical Services Branch |
Australian Bureau of Statistics

(P) (03) 9615 7685   (M) 0422 65 35 26

(E) geoffrey.brent@abs.gov.au  (W)  www.abs.gov.au

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