Skip to content

The "Hidden Curriculum" assignment from UT Austin's Masters Causal Inference course, Spring 2022.

License

Notifications You must be signed in to change notification settings

nateybear/causal-inference-2022

Repository files navigation

R Hidden Curriculum Assignment

Your assignment is to replicate this GitHub repository and produce a report that describes patterns in INCARCERATION STATUS by race and gender in the year 2002, using NLSY97 publicly available data. To do this, you will need to create a data extract at the NLS Investigator website that pulls the variables of interest. Here is a screenshot to help you out:

MAKE SURE to read the Codebook tab to understand how your variables are coded!

Navigate to the Save/Download tab and use the Advanced Download feature to download a comma-delimited file (CSV). You may download the RData file instead if you wish, but my example code uses CSV files.

Grading

The deliverable that you turn into Canvas will be a URL linking to your GitHub repository. You will be graded based on having all of the following in your GitHub repository:

  • A build script that cleans the raw dataset and prepares it for analysis
  • A script that generates a plot using ggplot and saves it in the figures directory
  • A script that generates a summary table using kableExtra and saves it in the tables directory
  • A script that generates a regression output summary using stargazer and saves it in the tables directory
  • A brief report written in LaTeX that summarizes the patterns that you find. Use a formal and descriptive writing style. You will be graded on a genuine attempt at analyzing the results.

About

The "Hidden Curriculum" assignment from UT Austin's Masters Causal Inference course, Spring 2022.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published