Epilepsy affects 1% of the World population. Thus, the probability for one person is `c(Yes=0.01, No=0.99)`

. We can simulate `n`

persons with the following code:

```
<- function(n) {
epilepsy return(
sample(c("Yes","No"),
size=n,
replace = TRUE,
prob = c(0.01, 0.99)
)
) }
```

We are 97 people in the course, including me. To simulate a group like us we use

`epilepsy(97)`

```
## [1] "No" "No" "No" "No" "Yes" "No" "No" "No" "No" "No" "No"
## [12] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No"
## [23] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No"
## [34] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No"
## [45] "No" "No" "Yes" "No" "No" "No" "No" "No" "No" "No" "No"
## [56] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No"
## [67] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No"
## [78] "No" "No" "No" "No" "No" "No" "No" "No" "No" "No" "No"
## [89] "No" "No" "No" "No" "No" "No" "No" "No" "No"
```

We replicate the experiment to get 1000 samples of size 97

```
<- replicate(1000, epilepsy(97))
courses dim(courses)
```

`## [1] 97 1000`

Here `courses`

is a **matrix**, not a data frame. We have to use `[row, col]`

, not `[[column]]`

.

We got a lot of data, but very little information. We did not learn anything from the 97000 words. We want numbers, not words. We need a function that

- takes one column of
`courses`

, and - gives us an integer with the number of “Yes”

This is your mission. Write the code to produce a vector named `cases`

of size 1000, with the number of “Yes” in each column. If everything goes right you will get something *similar* to this:

`table(cases)`

```
## cases
## 0 1 2 3 4
## 356 376 190 69 9
```

`barplot(table(cases))`