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Number of bins = 1 + ceil ( log 2 ( n ) ) ( 1 ) where log 2 is log base 2 (
Number of bins ceillogn
where log is log base search google for help on how to do log of in Python As the sample
size increases so does the number of bins. The ceiling function ceil ensures that the result of the
logarithm is an integer. Then the width of each bin is estimated as
Bin Width Max Min: Number of bins
where Max and Min are respectively, the maximum and the minimum values.
Consider the following iterative process used to generate a dataset X
with
Your task consists of creating a python function called HWpTaskUCusername that works
as follows
To call your function, the user will type in the Python Shell, the name of the function
HWpTaskUCusername and the arguments variables a b and n sample size
UCusername is what you use to login to CANVAS.
Your function will then
o Set the initial value of X to and the initial value of Y to
o Compute and store the successive values of X in a list using Equations and This
should be done using a repetition structure for or while loop and Pythons append
builtin function for adding on to lists.
o Compute the number of bins based on the sample size and using the Equation
o Compute the width of each bin using Equation
ENED HW Spring
o Store the frequency distribution in Python as a list, ie the number of elements of X in
each bin. Complete this step using repetition structures for or while loop and Pythons
append builtin function. The goal is to generate a repetition structure that will adjust
based on the number of bins, see the third hint below for more guidance.
o Print the list with the frequency distribution to Python Shell
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