## Part I -- ggplot - Facets

The first part requires you to create plots with faceting.

1. Read in the cleaned patients dataset, `patient-data-cleaned.txt`.

```{r}

```

1. Using the patient dataset generate a scatter plot of BMI versus Weight, add a
colour scale to the scatterplot based on the Height variable, and split the plot 
into a grid of plots separated by Smoking status and Sex.

```{r}

```

2. Generate a boxplot of BMIs comparing smokers and non-smokers, colour boxplot
by Sex, and include a separate facet for people of different age.

```{r}

```

3. Produce a similar boxplot of BMIs but this time group data by Sex, colour by Age and facet by Smoking status.

```{r}

```

4. Regenerate the solution to exercise 3 but this time using a violin plot.

```{r}

```

5. Generate density plots of BMIs coloured by Sex, and split the plot by Grade.

```{r}

```

## Part II -- tidyr - Tidying a dataset

1. Read in the simulated clinical dataset, `clinical-data.txt`.

```{r}

```

2. What are the variables in this data set?

```
Type your answer here
```

3. Transform the data into a tidy form using the `gather` function from the `tidyr` package.

```{r}

```

4. Display the range of values for each drug and placebo treatment as a box plot

```{r}

```
