Exercise

# One last box plot

You can also calculate new variables that don't directly show up in your data frame. Say for example you want to create a box plot of the sum of *weight* and *height* versus gender. This is of course nonsense, but it can be done like this:

```
w_height <- cdc$weight + cdc$height
boxplot(w_height ~ cdc$gender)
```

Notice that the first line above is just some arithmetic, but it's applied to all 20,000 observations in `cdc`

. That is, for each of the 20,000 participants, we take their weight and add it to their height. The result is 20,000 sums, one for each respondent. This is one reason why we like R: it lets us perform computations like this using very simple expressions.

Now let's try a more meaningful calculation.

Instructions

**100 XP**

- Consider the
**Body Mass Index**(BMI). BMI is a weight to height ratio and can be calculated as:

$$BMI = \frac{\mathrm{weight(lb)}}{\mathrm{height(in)}^{2}} \times 703$$

- Calculate the BMI for each respondent and assign the result to
`bmi`

. - Draw a box plot of the BMI versus the general health of the respondents.