Week 1

This week is designed to be an introduction week. We will briefly discuss topics related to statistics and inference. Then we will look at installing R and RStudio as well as the basics of using R.

January 17, 2023

Learning Outcomes

First Lecture

  • Installing R and RStudio

  • Scripts

  • R Calculator

  • Types of Data

Second Lecture

  • R Objects

  • R Functions

  • R Packages

Important Concepts

First Lecture

Accessing R & RStudio

If you are on a tablet or Chromebook, you can access R & RStudio via https://posit.cloud/ for free. However, they have limited computing resources. Be mindful of your experimentation. You may also be able to use Quarto in Rstudio cloud.

You can install R via their website: https://www.r-project.org/.

You can install RStudio for free from their website: https://posit.co/download/rstudio-desktop/

Using R

R can be used as a calculator; below are a few examples:

[1] 3
[1] 0.75
[1] 72
[1] 54.59815

Types of Data


These types of data are stored as a number in R. They may be whole numbers or contains decimal values known as double.


This type of data is stored a string of character values. They are usually surrounded by quotes in the output.


This type of data indicates TRUE or FALSE data. It is binary data.


This indicates that a value is missing or not computed. Commonly stored as NA or NaN.

Second Lecture

R Functions

R has specialized functions that can compute specific values. R functions require inputs, known as arguments, to produce a specific output.

For example, the log() function can be used to compute the natural logarithm of a specified input:

[1] 3.526361

If you want to know information about a specific function, you can use the ? operator:


which will open the help tab. Notice there are 2 arguments: x and base. This means that the log() function can be extended to other base. To use common log1, specify the arguments:

log(x=34, base=10)
[1] 1.531479

Notice that I specified the arguments. You can also type this:

log(34, 10)
[1] 1.531479

which produces the same results. This is because R uses positions in the function to determine argument values; therefore, if the positions are correct, you do not need to specify the argument name.

Going back to the First Lecture example, log(34), we did not specify the base. This is because functions have default values for arguments. The help documentation tells us what arguments have defaults and do not need to be specified.

R Objects

Install packages

You can extend the functionality of R. The tidyverse package includes a popular set of R packages for data wrangling and analysis. To install tidyverse, use the install.packages() function2:


Once you installed the R package, you will need to load with every R session using the library() function:



Lecture Slides Videos Files
1 Slides NA NA
2 Slides NA Examples General Script


  1. \(\log_{10}(x)\)↩︎

  2. The package name must be inputted with quotes in the function.↩︎