Exercise

# Calculating the mean and variance of a sample

Now that you're familiar with working with coin flips using the `binom`

object and calculating the mean and variance, let's try simulating a larger number of coin flips and calculating the sample mean and variance. Comparing this with the theoretical mean and variance will allow you to check if your simulated data follows the distribution you want.

We've preloaded the `binom`

object and the `describe()`

method from `scipy.stats`

for you, as well as creating an empty list called `averages`

to store the mean of the `sample`

variable and a variable called `variances`

to store the variance of the `sample`

variable.

Instructions 1/3

**undefined XP**

- Inside a loop, create a
`sample`

variable with 10 trials of 10 coin flips with 25% probability of getting heads.