Day 1 Exercise - Getting Comfy with R

In-Class Activity: Your First R Session

Goal: To become familiar with the RStudio interface and perform a basic data exploration workflow.

Create a new Markdown Document

  1. Go to File > New File > R Markdown

  2. Provide the title “Day 1” and input your name as the author

  3. A script will open in the Source pane. Remove unnecessary code.

  4. Go to File > Save and name it introduction.Rmd. Make sure this saves in the same folder as all of your other stuff. Stay Organized!

    1. I’m not going to tell you how to organize your folders, but I will give a suggestion. Have 1 folder for the whole class. This will have the Project that we created. Inside there, have a folder for “Class Activities”. This is where you can save this file. Then, have other folders for the labs and what not.

Starting the document

In the text field of the markdown file, introduce yourself! Answer these questions below:

  • Name:

  • Pronouns

  • Year in school

  • PhD/Thesis/Capstone

  • Area of psychology

  • Research interests

  • Comfort with R (1-10 with 10 being “Expert”)

  • Overall feelings toward Statistics

  • Anything else you want to share

Your First “Analysis”

  1. Create a Code Chunk

  2. Load the tidyverse library

  3. Create the object datawars and assign dataset called starwars to it (hint: data <- cars)

  4. Use View(), head() and glimpse() to look at datawars

  5. In the text below, answer these questions:

    1. What do each of these do?

    2. Which do you like more?

  6. Create another code chunk and use summary() to get descriptives of all variables in the dataset.

    1. Look at the output of your summary() command. For the mass and height variables, you’ll see a value for NA's. In your own words, what do you think NA means in this context?

Visualize your data

Now we want to investigate the relationship between mass and height in this dataset.

  • Create a scatterplot using ggplot().

  • The plot should show height on the x-axis and mass on the y-axis.

  • Add some labels to make your plot clear and professional.

    • Hint: Use the code below as a template and fill in the blanks.
ggplot(data = __, aes(x = __, y = __)) +
  geom_point() +
  labs(title = "__",
       x = "__",
       y = "__")
  • Look at your plot. Do you notice any characters that seem unusually heavy for their height? Briefly describe one.

Wrangle your Data

Since we have some outliers that seem to be related to non-human species, let’s just look at Humans.

  1. Create a new object called rebels.

  2. This new object should contain only the characters from the starwars dataset where the species is “Human”.

    • Hint: Use the filter() function. The syntax is new_object <- old_object %>% filter(column_name == "value"). Remember that “Human” needs to be in quotes.

  3. Print your new rebels object to the console to make sure your filter worked correctly. Once confirmed, calculate the average (hint: use mean()) for the height and weight of the rebels.

  • How many rows are in your new rebels dataset?

  • What is the average height and weight?

  1. Create another scatterplot with your new dataset. Copy and update the code we used previously.

Closing out the Document

What is 1 thing you are looking forward to this semester and 1 thing that you are worried about (can be in or outside of this class)?

End of the document. Remember to Knit and upload to myCourses.