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**:

- We need to import
`binom object`

from`scipy.stats`

. `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`

.- In the output we can see an array with five results for each coin
**with the number of successful trials for each coin**.

# Task

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:

- Import the
`binom`

object from`scipy.stats`

. - 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`

.

- Set

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