我正在努力
到目前为止,我得到的是:
import pylab
import random
sampleSize = 100
## Let's simulate the repeated throwing of a single six-sided die
singleDie = []
for i in range(sampleSize):
newValue = random.randint(1,6)
singleDie.append(newValue)
print "Results for throwing a single die", sampleSize, "times."
print "Mean of the sample =", pylab.mean(singleDie)
print "Median of the sample =", pylab.median(singleDie)
#print "Standard deviation of the sample =", pylab.std(singleDie)
print
print
pylab.hist(singleDie, bins=[0.5,1.5,2.5,3.5,4.5,5.5,6.5] )
pylab.xlabel('Value')
pylab.ylabel('Count')
pylab.savefig('singleDie.png')
pylab.show()
## What about repeatedly throwing two dice and summing them?
twoDice = []
for i in range(sampleSize):
newValue = random.randint(1,6) + random.randint(1,6)
twoDice.append(newValue)
print "Results for throwing two dices", sampleSize, "times."
print "Mean of the sample =", pylab.mean(twoDice)
print "Median of the sample =", pylab.median(twoDice)
#print "Standard deviation of the sample =", pylab.std(twoDice)
pylab.hist(twoDice, bins= pylab.arange(1.5,12.6,1.0))
pylab.xlabel('Value')
pylab.ylabel('Count')
pylab.savefig('twoDice.png')
pylab.show()
有谁能帮我画出cdf吗?在
您可以直接使用直方图绘制功能来实现这一点,例如
注意新行:
^{pr2}$应直接给出cdf图。如果不指定normed=1,您将看到表示百分比的刻度(0-100),而不是通常的概率刻度(0-1)。在
还有其他的方法。例如:
注意,现在我们对数组进行排序,构建函数并绘制它。在
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