4.8 Python Probability Practice Lesson 08

Some methods interesting to take notes.

4.8.0.1 .random.randint()

Generates a random value.

np.random.randint(0, 2, size=10000)

In the example above, the line code will generate a sample of 10,000 number from 0 to 1 (the 2 is not inclusive).

4.8.0.2 .random.choice()

Generates a radom value with different loads.

np.random.choice([0, 1], size=10000, p=[0.8, 0.2]))

In the example the loads are 0.8 and 0.2.

4.8.0.3 random.binomial()

This method is an other way to simulate a coin flip.

np.random.binomial(10, 0.5, 1000000)

The example above will flip 10 coins (with a fair rate due to the 0.5), with a sample of 1 million.

The result of this methods is a “aggregation” of the success events, which means the output varies from 0 to 10.

 

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A work by AH Uyekita

anderson.uyekita[at]gmail.com