[Edu-sig] teaching Python

Daniel Ajoy 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)
>  48.5
> 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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