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.
Published

August 24, 2025

Learning Outcomes

First Lecture

  • Define Population

  • Define Sample

  • Define Inference

  • Define Association

Second Lecture

  • Installing R and RStudio

  • Scripts

  • R Packages

  • R Environment

Resources

Lecture

Tuesday Slides | Thursday Slides

Videos

Section Tuesday Thursday
001
002

Important Concepts

First Lecture

Population

A set of all measurements of interest to the sample collector.

Sample

A sample is any subset of measurements selected from the population.

Inference

  • Parameter: a measurement describing the population

  • Statistic: a measurement describing the sample

Association

An association describes the relationship between two characteristics of a population.

Second Lecture

Accessing R & RStudio

If you are on a tablet or Chromebook, you can access R & RStudio via rstudio.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://www.rstudio.com/products/rstudio/download/

Using R

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

1+2
[1] 3
3/4
[1] 0.75
9*8
[1] 72
exp(4)
[1] 54.59815

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:

log(34)
[1] 3.526361

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

?log

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.

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:

install.packages('tidyverse')

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

library(tidyverse)

Footnotes

  1. \(\log_{10}(x)\)↩︎

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