Loading the Data

Before we can create any visualizations, we need data. We will work with data on a variety of subjects in this course. In statistics, sometimes we work with data that is very recent and sometimes we work with data from the past to detect trends that might inform future decisions. Today, we will be working with historical data.

To load the data, you need to create a Code Chunk (chunk for short). Remember that to do that, there are two options:

• Option 1: Look at the top of your Markdown file, and find Code. Click it. From the drop-down menu, choose Insert Chunk. Click it! A gray box should appear in your Markdown file. This is a chunk.
• Option 2: In the top gray bar of your Markdown file, look for a small green C (shown below). Click that, and choose R! A gray box should appear in your Markdown file. This is a chunk.

When you are done, you should have a code chunk that looks like this:

Once you have created your chunk, copy and paste the following inside the chunk. Note: You will need to scroll in the box below to get the whole code that you need to copy.

derbyplus <-read.csv("https://raw.githubusercontent.com/proback/BYSH/master/data/derbyplus.csv")

Now, look at the right hand side of the chunk and find the little green triangle symbol. We will call this the play button in this course. Go ahead and press the play button (press play). This tells R to run the code!

Once you have pressed play, look at the upper right hand panel of your RStudio screen (your Environment tab). Do you see that you have an object called derbyplus? This means that you have loaded the data set you need!

Next to the name derbyplus, you will see that R tells us the data set has 122 observations and 5 variables. This means that the data set has 122 rows and 5 columns.

If you click on the name derbyplus in the Environment, a spreadsheet showing the data set itself will appear. You can scroll through this spreadsheet to see the entire data set.

Answering the lab questions

Now that we have the data loaded, let’s answer our first lab question. Remember, to create a lab question you want to start a new line and put two ## in your RMarkdown document, hit the space bar, and then type Question 1. This means you should see ## Question 1. Then, hit enter (or return if you are on a Mac) twice, and you are ready to answer the questions!

The ## allows your Question numbers of show up in bold so I can easily find them for grading. The * puts your text in italics. Let’s try it!

Data Summary

Our data for today relates to the Kentucky Derby, a famous horse race that takes place every year in Kentucky. Our data contain information on the winning horse of each Derby.

Our focus for today is on exploratory data analysis, or EDA. This means using graphs and tables to explore a data set. One powerful tool we use in EDA is a data summary. This is a way to very quickly get an idea of what information is contained in the data set.

To create a data summary, create a chunk, type the following, and then press play:

summary(derbyplus)

Welcome to your first R command! In R, the format for coding is command(object). In other words, the command tells R what you want to do. The command summary tells R we want to create a summary of a data set. The object piece tells R what object or data set you want the command to work with. So, summary(derbyplus) tells R we want to see a summary of the derbyplus data set.

We can see that the summary gives us a quick overview of what variables are in the data set and what information those variables provide. The summary is really useful, but sometimes we still have to look at the data itself to answer certain questions.

Installing ggplot2

To create plots in R, we need to install the ggplot2 package. A package is collection of R codes that relate to one another. When you load a package into R, you give R access to all of the functions within the package. We will be using several packages as we move through this class.

Go to the top of your RStudio window and find “Tools”. From there, click on “Install Packages.” In the blank box, type in ggplot2, and hit install. The computer should automatically begin to load in the packages that you need, but this may take a minute.

Once you have installed the package, create a chunk in your RMarkdown. Inside of the chunk, paste the code library(ggplot2), and hit play. You are now ready to begin creating graphs

Note: Some of you may see an error about language parsing, or an error involving rlang. If you do, go ahead and install the rlang package. Then, run the code library(rlang). Once this is done, install ggplot2 again.

Labels and Titles

We can add on another layer to our plot: x and y axis labels, as well as a title for the plot. The command labs, which stands for labels, is used for this.

ggplot(derbyplus, aes(x=condition)) + 
     geom_bar(fill='blue') + 
     labs(title="The title you want", 
     x = "The x-axis label", y = "The y-axis label")

Considering Speed: Histograms

Now that we have explored the track condition, let’s try another variable. A second variable in our data set is speed, which represents the feet per second of the horse that won the Derby in a particular year.

To visualize the distribution of the variable speed, we are going to use a plot called a histogram. Paste the following code in a chunk and hit play.

ggplot(derbyplus, aes(x=speed)) + 
    geom_histogram(bins = 10, fill='cyan', color= 'white')

Comparing Speed and Number of Starters

Suppose we are asked to explore the relationship between X = the number of horses that ran in a race (starters) and Y = the speed of the winning horse (speed). This means that we need to look at two different variables in the data set: starters and speed.

Both winning speed and number of starters are numeric variables, so as we learned in class a scatter plot is a good choice to explore the relationship between the two variables. To make a scatter plot, create a new chunk and run the following code:

ggplot(derbyplus, aes(x=starters, y = speed)) + geom_point()

Just as before, we have two layers. The first draws the background and the second adds on the data. Here, in the first layer, we specify both the x and y axis of the graph, as we have two variables that we are working with.

Now that we have our graph, we are going to describe the relationship we see in the graph.

Turning in your assignment

When your Markdown document is complete, do a final knit and make sure everything compiles. You will then submit your document on Canvas. You must submit a PDF or html document to Canvas. No other formats will be accepted. Make sure you look through the final document to make sure everything has knit correctly.