miku/README.md

## README.md

      
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A conditional probability is a probability based on
some background information - that make up a condition.
The cookie problem

Suppose there are two bowls of cookies. Bowl 1 contains 30 vanilla cookies and
10 chocolate cookies. Bowl 2 contains 20 of each. Now suppose you choose one of
the bowls at random and, without looking, select a cookie at random. The cookie
is vanilla. What is the probability that it came from Bowl 1?
The diachronic interpretation

p(H|D) = P(H) * (D|H) / P(D)

p(H): prior
p(H|D): posterior
p(D|H): likelihood, probability of the data under the hypothesis
p(D): normalizing constant

The normalizing constant can be tricky. It is supposed to be the probability of
seeing the data under any hypothesis at all, but in the most general case it is
hard to nail down what that means.

  
## bayes.py
#!/usr/bin/env python

"""
Example code.
"""

if __name__ == '__main__':
    print("Hello World")
	#!/usr/bin/env python

	"""
	Example code.
	"""

	if __name__ == '__main__':
	print("Hello World")