hw01_gapminder.Rmd

---
title: "hw01_gapminder"
author: "Thomas Smith"
date: '2018-09-18'
output: github_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

## Introduction

This document is part of Assignment 1 for STAT 545A course taught at the University of British Columbia. This component of the assignment is to demonstrate the student's ability to create an R Markdown file, and use it to explore a dataset. For this assignment, I have decided to use the 'mtcars' dataset. 

## Data exploration

We can see the dataset as a whole:

```{r}
mtcars
```

Or look at the first 6 rows:
```{r}
head(mtcars)
```

Or last six rows:

```{r}
tail(mtcars)
```


We can also look at specific attributes of this dataset, such as:

### Structure

```{r}
str(mtcars)
```

### Class

```{r}
class(mtcars)
```
 
### Variables

```{r}
names(mtcars)
```

We can see general dimensions of the dataset with, shown as rows, then collumns:

```{r}
dim(mtcars)
```


Or specfically the rows included.

```{r}
nrow(mtcars)
```

And if we want a summary of statistics, it's simple!

```{r}
summary(mtcars)
```

## Data Visualization
Although we have not gotten too into detail in regard to data visualization, here are some basic functions. This is horsepower (hp) plotted with number of cylinders (cyl).

```{r}
plot(cyl ~ hp, mtcars)
```

Or 1/4 mile time (qsec) plotted with horsepower (hp)...
```{r}
plot(hp ~ qsec, mtcars)
```

We can even make histograms. This shows the frequency of cars in the dataset with different number of cylinders.
```{r}
hist(mtcars$cyl)
```

And there you have it, some fun data exploration using R Markdown!