Gnumeric vs Excel
nes...@wigner.berkeley.edu
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"The open source spreadsheet package "Gnumeric" was such a good clone
of Microsoft Excel that it even had errors in its statistical functions
similar to those in Excel's statistical functions. When apprised of the
errors in v1.0.4, the developers of Gnumeric indicated that they would
try to fix the errors. Indeed, Gnumeric v1.1.2, has largely fixed its
flaws, while Microsoft has not fixed its errors through many successive
versions. Persons who desire to use a spreadsheet package to perform
statistical analyses are advised to use Gnumeric rather than Excel."
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http://web.archive.org/web/20040412052948/http://www.csdassn.org/software_reports/gnumeric.pdf
Roy Schestowitz
There is no word which discourages the use of KSpread or Calc, to name just
two 'opponents'. And then you can come to consider Web-based equivalents;
either third-party (e.g. Google Spreadsheets), or FOSS software installed
locally (even on a public domain for collaboration). Here is what I use:
http://freshmeat.net/projects/phpwebsheet/
Best wishes,
Roy
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Linonut
> __/ [ nes...@wigner.berkeley.edu ] on Tuesday 06 June 2006 22:19 \__
>
>> Abstract:
>> --------------------
>> "The open source spreadsheet package "Gnumeric" was such a good clone
>> of Microsoft Excel that it even had errors in its statistical functions
>> similar to those in Excel's statistical functions. When apprised of the
>> errors in v1.0.4, the developers of Gnumeric indicated that they would
>> try to fix the errors. Indeed, Gnumeric v1.1.2, has largely fixed its
>> flaws, while Microsoft has not fixed its errors through many successive
>> versions. Persons who desire to use a spreadsheet package to perform
>> statistical analyses are advised to use Gnumeric rather than Excel."
>> --------------------
>>
> http://web.archive.org/web/20040412052948/http://www.csdassn.org/software_reports/gnumeric.pdf
Interesting.
Poisson distribution:
"In Excel 20003, Microsoft obtained an accurate answer in the
central region of the distribution in exchange for inaccurate results
in the tail. This is not a good "fix". A good fix is demonstrated
by gnumeric."
Hypergeometric distribution:
"Microsoft did not fix Excel."
Standard normal distribution:
"Microsoft did not fix Excel."
Inverse normal distribution:
"Microsoft traded a weak algorithm for one that was slightly less
weak."
Inverse chi-square distribution:
"Microsoft did not fix Excel."
Inverse F distribution:
"Microsoft did not fix Excel."
Inverse t distribution:
"Microsoft did not fix Excel."
Inverse beta function:
"...Microsoft claims to have fixed the inverse beta function."
Not.
Sample standard deviation (benchmark tests):
"Excel consistently does a poor job... Microsoft did not fix the
problem in Excel."
ANOVA (benchmark tests):
"Excel's performance on this suite of tests is unacceptable."
Linear regression (benchmark tests):
"Either way, returning zero digits of accuracy is unacceptable...
Microsoft did not fix Excel."
Random number generator:
"Gnumeric RNG is based on '/dev/urandom' ... This is a very good
method to obtain seeds for pseudo-random numbers, but it is not a
good way to generate random numbers for statistical purposees... can
be judged unacceptable for statistical purposes."
"The random number generator in Excel has been examined... and found
to fail Marsaglia's DIEHARD tests."
----------------------------------
My jaw dropped reading this, as I started to wonder just how much
research is based on numbers produced by Excel's stat routines, and just
how responsive a small cadre of open-source developers was/is compared
to mighty Microsoft.
(I'm also going to take a look at my own linreg algorithm!!!)
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nes...@wigner.berkeley.edu
distinct from what they used to call systems programming. For example,
programming an inverse chi square distribution function that works
accurately and efficiently is quite different from writing a function
that deals only with string and integer quantities. The required
skills are taught in computer science departments, but probably the
people who managed Excel didn't know anything about them and didn't
care. It's really a sign of sloppy management. The litany that
Linonut cites is pretty damning.
I know a guy who is on a crusade regarding floating point processors.
The standards developed for these things in the 80's took a lot of
thought, and in some cases were painful for the engineers to implement.
Now these standards are being abandoned by manufacturers (IBM was
mentioned in a talk I heard), because they're too much trouble to
implement and because for gaming applications it doesn't matter if a
floating point operation makes an occasional error. But these same
chips are also being advertised as being useful for number crunching
(designing bridges, space shuttles, etc).