Course Content

# Probability Theory

3. Conducting Fascinating Experiments

5. Normal Distribution

Probability Theory

## Binomial probability 2/2

Look at the code example of the binomial probability

Explanation of the code above:

1. We need to import `binom object` from `scipy.stats`.
2. `binom.rvs(p = 0.5, size = 5, n = 3)` means that the probability of getting head is 50 %, `p = 0.5`; the size of sample in experiment is 5, `size = 5`; the number of trial is 3, `n = 3`.
3. In the output we can see an array with five results for each coin with the number of successful trials for each coin.

Your task here is almost the same as in the previous chapter, play with one coin!

Imagine that here you have a coin with a general probability of 50%. Follow this algorithm:

1. Import the `binom` object from `scipy.stats`.
2. Conduct the experiment with `binom` object using `rvs()` function:
• Set `p` parameter equal to `0.5`.
• Set `size` parameter equal to `1`.
• Set `n` parameter equal to `5`.

Please note, you can comment on the line where `np.random.seed()` was defined and "play with the coin" to receive various outputs.

Note

Explanation of the output : We were tossing one coin five times, and it only led to success in three cases.

Everything was clear?

Section 1. Chapter 5