[Edu-sig] teaching Python
dajoy at openworldlearning.org
Sun Nov 28 23:36:44 CET 2004
I've always wanted to teach myself *inferential* statistics
through programming, but most of the examples of statistics
being taught through programming are *descriptive* statistics.
Most of the simple programs that you see in old BASIC books
that deal with statistics are, descriptive statistics.
Most *inferential* statistics algorithms are overly technical
or boring, and don't contribute to the understanding of
inferential statistics. Eg, chi-square-distribution algorithm.
I'm thinking that the problem arises because inferential
statistics deal with population with an infinite number of
members, or infinite many samples.
On 28 Nov 2004 at 12:00, edu-sig-request at python.org wrote:
> For example, when doing stats, it's common to want a list of random numbers.
> It'd be useful to have a function with three parameters: min and max to
> specify the range for the random integers, and a howmany.
> >>> from random import randint
> >>> def getrand(min, max, howmany):
> return [randint(min,max) for i in range(howmany)]
> >>> mylist = getrand(0,100,10)
> >>> mylist
> [0, 58, 53, 47, 89, 61, 60, 87, 12, 18]
> Then we could do stuff like:
> >>> def mean(somelist):
> return sum(somelist)/float(len(somelist)) # or use truedivision
> >>> mean(mylist)
> Then on to standard deviation, divergence, and so on. Very short programs.
> Lots of command line exploration. Then save the short programs in a module
> for reuse later.
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