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Re:You Can’t Do Data Science in a GUI by haZard_OS on Sunday April 15, 2018 @11:44PM (#16846533)
Can you? I have long been under the impression that Excel is to be avoided for all but the lightest, most cursory analyses.

From 2007:

http://people.umass.edu/evagold/excel.html

From 2013:

http://biostat.mc.vanderbilt.edu/wiki/Main/ExcelProblems

I could post more but I would have to fire-up my old spreadsheet ;)

Re:You Can’t Do Data Science in a GUI by CJefferson on Monday April 16, 2018 @08:43AM (#16848520)
I opened your second link. The first issue is the classic floating point numbers have rounding errors problem, which as far as I know, every system suffers from. That isn't just an excel problem.
Re:You Can’t Do Data Science in a GUI by ska on Monday April 16, 2018 @09:57AM (#16848996)
The problem is often related to floating point representation, that is true, but it's not correct to conclude "oh well, everything gets this wrong so I might as well use excel".

One issue with excel is that many of the built in functions and statistical measures are implemented in numerically naive ways (and presumably remain so for reasons of computation speed and backwards compatibility) so if you want to do robust analysis you have to avoid them entirely - at which point you are far better off with a language designed for this. This is particularly an issue with larger data sets, where accumulation errors can become acute. Excel also introduces additional error terms due to binary encoding.

By the way: it is misleading to think of "rounding error problems". Far better to think about it as "rounding properties"/"truncation properties" and the like, then realize that you can't (in general) write floating point operations as if they were utilizing real numbers and expect correct behavior. That doesn't mean correct behavior is not achievable.