Exercise

# Flipping an unfair coin

Until now you've been running simulations where each outcome had an equal probability. However, the `sample()`

function also allows you to set the probabilities.

You can set these probabilities by adding an argument called `prob`

to the `sample()`

function. This argument needs a vector of probability weights, one for each possible outcome. An example of such a vector for three possible outcomes is `c(0.1, 0.6, 0.3)`

.

Note that for the fair coin the probability weight vector is `c(0.5, 0.5)`

. The default of the `sample()`

function (when no `prob`

is given) is for all outcomes to have equal probability.

Instructions

**100 XP**

- Run 100 simulations of an unfair coin that lands on head 20% of the time. Do this by assigning assign the result to
`sim_unfair_coin`

. (If you need help, look at the documentation by typing`?sample`

in the console.) - Inspect the result using the
`table()`

function.