## 4 – Python Probability Conclusion

In this lesson, you put your new probability skills to practice using Python. In order to gain an understanding of some of the complex topics in the next sections, we’ll be working with Python more and more. It’s often easier to understand these complex ideas through simulations and Python than it is to prove them … Read more

## 3 – Simulating Many Coin Flips

So far, we’ve been stimulating event outcomes by generating random numbers with NumPy’s random.randint and random.choice. However, there is a better function for simulating large binomial experiments like coin flips. Here, you see NumPy’s random.binomial function, which simulates a number of events n, which each have probability of success p. Success just represents one of … Read more

## 2 – Simulating Coin Flips

NumPy has a module for random sampling, that makes it really easy for us to simulate random events like coin flips and Python. We’re going to start with a simple example, simulating a single coin flip. For this, we’ll use a function called randint. This generates however many random integers, we specify between a lower … Read more

## 1 – Python Probability Introduction

Now that you’ve seen some examples and the math involved with them, you’re going to apply this knowledge to problems using Python. This lesson includes screencast and Jupyter notebooks to help you practice using Python to explore the topics of probability you just learned. Let’s get started.