---
title: "Assignment 2"
author: "Andrew Hayes, id = 21321503"
date: "`r format(Sys.time(), '%d %B, %Y')`"
output:
  word_document: default
  pdf_document: default
---

## Starting with R-Markdown

In the following R-Markdown document some data are created followed by calculation of some summary statistics and display of graphical summaries. All the results are embedded for you in the report when you `knit` the document into a report.

The following `R` chunk creates a dataset in a vector and stores it in `R`'s memory using the name `x`. You will have been given some directions in how to adapt this dataset on Blackboard.

```{r}

x = c(10, 23, 14, 12, 34, 26, 28, 24)

```

The mean of this data is

```{r}

mean(x)

```

The summary statistics (minimum, maximum, $Q_1$, median, mean and $Q_3$) obtained from the `summary()` function are:

```{r}
# Insert your code here
summary(x)



```

The five number summary which uses Tukey's method to estimate the lower and upper quartiles ($Q_1$ and $Q_3$) is given below. Notice the small differences in these quartiles.

```{r}
# Insert your code here
fivenum(x)



```

The boxplot of the data below also uses Tukey's method. I would describe the shape of the distribution using the boxplot as right-skewed, as the tail on the right is significantly longer than the tail on the left. However, the median is offset to the right of the box, which would normally indicate a left-skew. One possible reason for this inconsistency is the small size of the dataset used for this boxplot, as boxplots are not very accurate for small data sets.

```{r}

boxplot(x)

```

A histogram is given below. I would describe the shape of the distribution using the histogram as right-skewed, as it peaks on the left, and decreases as it goes to the right.
```{r}
hist(x)
```









Use the help system in `R` to learn how to use the `breaks` argument in the `hist` function to include around 10 breakpoints. To use the help system type `help(hist)`
```{r}
hist(x, breaks = 10)
```




