I have a model program for Python to find the varience of the wolf's dice.

My instructor asks me to do this:

1. Add a variable called tail_r (for "tail of the red-die distribution"). This variable should initially equal zero. Each time through the loop, if v is greater than or equal to Vr, then add 1 to tail_r. Thus tail_r will count the number of repetitions in which the simulated variance is at least as large as the observed one. Before you modify the code, think carefully. Where should tail_r be defined and initialized? Inside the inner loop? Before the inner loop but inside the outer one? Or before both loops?

this is the model program:

from random import random # line number 1

# define a function to return the variance of values in xvec # 3 def var(xvec): # 4 m = msq = 0.0 # 5 for x in xvec: # 6 m += x # 7 msq += x*x # 8 n = float(len(xvec)) # 9 m /= n # mean # 10 msq /= n # mean square # 11 return (msq - m*m) # variance # 12

w = [3246, 3449, 2897, 2841, 3635, 3932] # counts from white die # 14 r = [3407, 3631, 3176, 2916, 3448, 3422] # counts from red die # 15

Vw = var(w) # 17 Vr = var(r) # 18 print "Var(white):", Vw # 19 print "Var(red) :", Vr # 20

nreps = 10 # adjust this to do more replicates # 22 for rep in xrange(nreps): # 23 count = [0,0,0,0,0,0] # count[i] accumulates the numbers of # 24 # rolls that showed i+1 spots # 25 for roll in xrange(20000): # do 20000 rolls of the simulated die # 26 spots = int(6.0*random()) # uniform on [0,1,2,3,4,5] # 27 count[spots] += 1 # here's the accumulation # 28

v = var(count) # and here's our function call # 30

print "Repetition %d: var=%f" % (rep, v) # REMOVE ME later # 32