A Journey from Wild to Textbook Data to Reproducibly Refresh the Wages Data from the National Longitudinal Survey of Youth Database
Dewi Amaliah, Dianne Cook, Emi Tanaka, Kate Hyde, Nicholas Tierney

TL;DR
This paper details the process of updating a wages dataset from the NLSY79 for teaching purposes, emphasizing reproducibility and providing tools for ongoing updates.
Contribution
It introduces a reproducible workflow and open-source R package for regularly refreshing a key educational dataset from longitudinal survey data.
Findings
Successfully refreshed wages data from NLSY79 up to 2018
Provided open-source tools and documentation for reproducible updates
Facilitated the use of contemporary data in teaching statistics and data science
Abstract
Textbook data is essential for teaching statistics and data science methods because they are clean, allowing the instructor to focus on methodology. Ideally textbook data sets are refreshed regularly, especially when they are subsets taken from an on-going data collection. It is also important to use contemporary data for teaching, to imbue the sense that the methodology is relevant today. This paper describes the trials and tribulations of refreshing a textbook data set on wages, extracted from the National Longitudinal Survey of Youth (NLSY79) in the early 1990s. The data is useful for teaching modeling and exploratory analysis of longitudinal data. Subsets of NLSY79, including the wages data, can be found in supplementary files from numerous textbooks and research articles. The NLSY79 database has been continuously updated through to 2018, so new records are available. Here we…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsData Analysis with R · Online Learning and Analytics
