Pre-work

Install R and RStudio

  1. Download R from CRAN. Choose the link at the top that corresponds to your operating system. Unless you downloaded R within the past month or two, do so again – you want the most up-to-date version (≥ R 4.3) for this class.

  2. Download RStudio (step 2 on that page – you already completed step 1 above!). It should automatically recognize your operating system, but if not, choose the correct link at the bottom.

If you have a Mac, make sure you choose correctly between the Apple Silicon (M1/M2) and Intel options.Which version of RStudio you have is not as important, but it’s nice to stay up-to-date for the newest features!

Video

Open the slides in a new tab here or follow along below.

(P.S. Sorry, I didn’t realize the video of my face would be in the screen instead of off to the side!)

Readings

  1. Sections 1.4-1.5 of R for Data Science. Run the code in your RStudio console as you go.

  2. Chapter 3 of R for Data Science. Again, run the code in your RStudio console as you read. Try the exercises.

  3. Optional, but helpful: Chapter 2 of Hands-On Programming with R. For the purposes of this class, we will necessarily skip some of the R basics to focus on the skills you’ll need most. This is a good resource if you want to learn more about them, so it’s highly recommended, you just don’t need to master it as part of your pre-work.

In particular, make sure you install the packages in the text.If you’re wondering what happened to chapter 2, we’ll be doing that one together!

Homework

Complete the following exercises, showing your code for each. You can download the homework as a Word document here or on Canvas. Please copy and paste your code and answers into the document and submit on Canvas.

  1. Install R and RStudio as well as the packages described in Section 1.4 of of R for Data Science. Paste the code you used to install those packages below.
  2. Create a vector named temp with the average low temperatures in December for London, Shanghai, Sydney, Boston, Mexico City and Johannesburg which are 40, 38, 64, 28, 42 and 57° Fahrenheit.
  3. Create a second vector with the city names called city.
  4. Use the setNames() function to assign the city names to the corresponding temperatures using the two objects create above. (Hint: help(setNames)). You should overwrite your original temp vector with the named vector. Print the temp vector.
  5. Recall that you can use the [] operator directly following a vector name to select specific values contained within that vector (e.g. temp[1] should return 40). Use this [] operator and the sum() function to calculate the sum of the temperatures for Sydney, Mexico City and Johannesburg.
  6. Create a vector of all positive even numbers smaller than 75 using the seq() function. (Hint: help(seq))
  7. Create a vector of numbers. Let the first value of the vector be 4, with a maximum value < 80, adding numbers in increments of 2/3. How many elements are in this vector?
  8. Using your answer to the previous question, find another solution to create the same vector as the previous question.

Resources