2_Summary_stats.Rmd

---
title: "Exercise 2 - Summary statistics"
output: html_document
---

```{r load_libraries, include=FALSE}
library(tidyverse)
```

R has a number of inbuilt functions to calculate summary statistics. Each of them takes a set of 
numbers and reduces them down to a single summary value. For this exercise, we will be asking you
to work with two inbuilt datasets, `sleep` and `InsectSprays`.

```{r datasets}
#Learn about the datasets
?sleep
?InsectSprays
```


> Calculate summary statistics for each group in the data.

Calculate the:

* Mean - `mean()`
* Median - `median()`
* Variance - `var()`
* Standard deviation - `sd()`
* Interquartile range - `IQR()`

for each experimental group in the `sleep` and `InsectSprays` data set.

```{r summary_stats}
# Summarise sleep
sleep %>% 
  group_by(_____) %>% 
  summarise(_____)

# Summarise InsectSprays
InsectSprays %>% 
  _____
```

Are the summary statistics useful in understanding the data?

How does this compare with the plots of data distributions we have been producing?

```{r plotting_distributions}
# Boxplot for sleep data
sleep %>% 
  ggplot(aes(x = group, y = extra)) +
  geom_boxplot()

# Boxplot for InsectSprays data
InsectSprays %>% 
  _____
```