Elections

Part II: Computing on the Data

You can access the data from the 2009 Iran election in the iran data frame inside the stat20data package.

Question 1

What is the empirical distribution of the vote counts for Ahmadinejad? Answer with:

  • a plot (label your axes and provide a title),
  • numerical summaries of center and spread,
  • and a written interpretation.

Question 2

Create two vectors:

  • one with the range of values that the Benford’s Law probability distribution can take

  • and the second with the corresponding probabilities for each value.

Question 3

What might 366 draws (the amount of rows in the iran dataframe) from \(X \sim Benford()\) look like? Find out by sampling from the \(Benford\) probability distribution. Create a plot of the resulting empirical distribution that you collect. Label your axes and title your plot Benford’s Law Simulation.

Question 4

What do the first digit empirical distributions look like for the four candidates in the Iranian presidential election?

  • Make one plot for each distribution and title them by candidate name.
  • Combine the four plots into a single visualization using the patchwork library.

Inside the stat20data package there is a function called get_first() that pulls off the first digit of every element in a vector. This will be helpful when creating your plots.

Question 5

How do the observed first digit distributions of Question 4 compare to the one you created in Question 3 by sampling from Benford’s Law? Which candidate has a first-digit distribution that is:

  • most similar to
  • most different

from the sampled one?

US Elections

The OpenElections project obtains and standardizes precinct-level results from US elections, including the 2020 US Presidential Election. To access the data, visit OpenElections’ GitHub page (https://github.com/openelections) and click on the tab labeled “Repositories”. From there, scroll down and click on a link to a data repository for the state of your choosing (the repository for Oregon, for example, is called openelections-data-or.). Select the 2020 folder and find a file that ends in .csv. Some notes:

  • Each state uses a different format, so click through a couple states’ repositories until you find one that will allow you to study voting patterns at the precinct-level.
  • To read the csv file into R, you will need to point R to the raw version of the data set. To view the raw csv you will either click the button that says “Raw” at the top right of the data frame on GitHub or click the link that says “View Raw Data”. When you are looking at the raw csv file, the url in your browser is the one you can use to access the file from within R.
  • There may be strange extra rows in your data, such as a row tallying total overall votes. Visually inspect the data to see if anything jumps out and be sure to take this into consideration when doing your analysis.

Question 6

What state did you choose to study? What is the unit of observation in your state’s data frame? What are the dimensions?

Question 7

Use this data to create a plot of that state’s first digit distribution by precinct. Use the number of votes cast for Joseph Biden in each precinct.

Question 8

Does the election you chose appear to fit Benford’s distribution better or worse than the Iran election?

Question 9

Take this opportunity to explore the US elections data provided by Open Elections and construct a data visualization of your choosing. This plot could deal with vote totals for different candidates or different parties, the types of offices, how candidates appear on the ballots, how one state compares to another state, how a state or precinct has changed over time … you have lots of options here!

Once you have a plot, make two claims: a summary claim and a generalization. Do you think your generalization claim is well-supported here?

Last Question

Will you ensure that your submission to Gradescope…

  1. is of a pdf generated from a qmd file,
  2. has all of your code visible to readers,
  3. and assigns each of the questions to all pages that show your work for that question?

(This one is easy! Just answer “yes” or “no”)