Getting Started Tutorial

Student: “How do I learn R?”

Teacher: “By using it.”

Student: “But I don’t know how to use it.”

Teacher: “Just try it anyway. Suddenly you’ll understand.”

Most people that are new to using the “R Software” ask the question, “How do I learn R?” The answer is simple: “start using it.” Really. Seriously. Just start using it, even when you have no idea what you are doing, and suddenly you will start to learn R. So, here we go. The more you use it, the more you will know.

This textbook (the “Statistics-Notebook”) follows a simple learning model:

1. Hover your mouse over codeYes, just like that. By hovering over “Codes” you will get instructions on what that code does. to read about it.
2. Click on a line of codeHovering is a good start, try clicking on this one. to see what it does.

   

3. Try typing the code into RStudio yourself to actually start learning R. (This is the most important step! Avoid copying and pasting codes, and type them instead. The more you type codes yourself, even though it is slow and prone to mistakes, the more you will learn.)

In summary, the most successful students in Math 325 follow the pattern:

Example Codes

For each of the following examples: (1) hover, (2) click, and (3) try.

Before you begin working on these Example Codes, ensure you have RStudio open. It should look like this:

Example 1

Remember, “Hover” the code first, then click, then try.

View( The “View” R function (with a CAPTIAL ‘V’ in View) allows us to view a data set. When run, this function will open up a new tab in RStudio showing the data set. cars cars is a data set that is in R. R has datasets that are available for anyone to use. You can see them using the data() command. It would be good to explore View() for a few different datasets. ) Always be sure to end your function with closing parantheses.     
Press Enter to run the code.  Click to Show Tutorial  Click to see a full tutorial on the “View()” command.

Good work clicking on Example Code 1.

But… Did you remember to first hover your mouse over the View(cars) example code? Good job if you did.

If not, go do that right now before continuing.

R allows you to work with data. So, the first step to understanding R is to open a dataset and begin exploring some data.

If you type the data() command into your Console of RStudio you will see a list of “built in” data sets that come with R. Go ahead and type data() into your R Console (and then press Return or Enter) right now to try it yourself.

The cars data set is one of the options that is available within the list from the data() command. This is a fun “historic” data set from the 1920’s. It shows the speed and stopping distance of cars from the 1920’s.

To see the cars data set in RStudio, use the View command as follows.

Step 1. Open RStudio.

Step 2. Type the command View(cars) into your Console.

Step 3. Press Enter or Return and the following output should appear within RStudio.

Be sure to TRY IT yourself, if you haven’t already. Good work if you did. It’s the only way to learn R.

Ask someone for help if you aren’t sure how to get started.

Try View(airquality) as well.

Example 2

mean( An R function “mean()” that will compute the mean of a quantitative column of data from a data set. cars cars is the name of a data set in R. Any data set can be used instead by simply typing the name of that data set instead of cars. $ The $ sign is a powerful operator in R. The $ sign allows you to access, or “purchase,” any column from a data set. Try typing cars$ into R and notice how a selection menu appears with options dist and speed. dist dist is one of the two columns from the cars data set. By typing cars$dist we are essentially pulling that column of data out of the data set, and then computing the mean of that column with mean(cars$dist). ) Closing parenthesis for the mean() function.     
Press Enter to run the code.  Click to Show Output  Click to see output.

Did you remember to first hover your mouse over the mean(cars$dist) example code? Good job if you did.

If not, go do that right now before continuing.

Recall that you “Viewed” the cars data set in the first example code. If you look carefully at this data set, you should notice that there are two columns labeled speed and dist in this data set. Each row of the data set represents a vehicle that was going a certain speed (in miles per hour) and once the breaks were applied, the distance the vehicle took to stop was also recorded (in feet). This data was recorded for 50 different vehicles. So it might make sense to compute something like the average (or mean) distance it took vehicles to stop. This is done with the mean( ) function. Notice how the $ sign is used to access a column called dist from the cars data set. Think of the data set cars as a store, and if you bring your money $ then you can “buy” the column dist from that data set.

You may also be interested in trying any of the following:

• sd(cars$dist)
• var(cars$dist)
• median(cars$dist)
• min(cars$dist)
• max(cars$dist)
• length(cars$dist)
• sum(cars$dist)

If you are curious, you can begin exploring the Numerical Summaries page of your Statistics-Notebook to learn more. But we won’t officially get to that as a class until later this week. So you don’t need to worry about it for now.

Example 3

plot( The plot(...) function allows us to create a plot (usually a scatterplot) in R. dist dist is the name of a column from the cars data set. This is going to be the Y-variable of the plot. The Y-variable always comes first in the plot(Y ~ X) command.  ~  ~ is found on the upper-left key of your keyboard. It is called the “tilde” or “tilda” symbol. It is used to state a relationship between Y and X: Y ~ X. speed speed is the name of a column. This is going to be the X-variable of the plot. The X-variable always comes after the ~ in the plot(Y ~ X) command. ,  The comma , is used to separate each entry within a command. data=cars The data= statement is used to tell R which data set the columns of “dist” and “speed” come from. In this case, the cars data set. ,  The comma , is used to separate each entry within a command. col=“skyblue” The col= statement is used to tell R which color to use in the plot. Type colors() in your R Console to see what options there are. This code is using the "skyblue" color. Color names are always placed in quotes " ". ,  The comma , is used to separate each entry within a command. pch=16 The pch= statement is used to tell R which plotting character to use in the plot. Type ?pch in your R Console to see what options there are. (You’ll need to scroll down in the help file that appears until you get to the 'pch values' section. ) Closing parenthesis for the plot(…) function.     
Press Enter to run the code.  Click to Show Output  Click to View Output.

Study the image below.

Try changing the col="skyblue" statement to col="firebrick" instead. What do you notice?

Try changing the pch=16 statement to pch=4 or any other number from 1 to 25. What do you notice?

Hint: pressing the “up” arrow on your keyboard brings up the last command you typed into the Console.

Good work! You’re all done for now.

Completion Code: abc123R

Return to the R Commands page of the Statistics-Notebook.

This is “the end” of the Getting Started tutorial. To find the “completion code” you will need to study, and “click open” each of the example codes above.