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85c0609 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | # %%
# import libraries
import numpy as np
import matplotlib.pyplot as plt
# %%
# create a list of numbers to compute the mean and variance
x = [1,2,4,6,5,4,0,-4,5,-2,6,10,-9,1,3,-6]
n = len(x)
# compute the population mean
popmean = np.mean(x)
# compute a sample mean
sample = np.random.choice(x,size=5,replace=True)
sampmean = np.mean(sample)
# print them
print(popmean)
print(sampmean)
# %%
# compute lots of sample means
# number of experiments tor run
nExpers = 10000
# run the experiment!
sampleMeans = np.zeros(nExpers)
for i in range(nExpers):
# step 1: draw a sample
sample = np.random.choice(x,size=5,replace=True)
# step 2: compute its mean
sampleMeans[i] = np.mean(sample)
# show the results as a histogram
plt.hist(sampleMeans,bins=40, density=True)
plt.plot([popmean,popmean], [0,.3],'m--')
plt.ylabel('Count')
plt.xlabel('Sample mean')
plt.show()
# %%
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