Overview of the “Syntucky” data for the participants of the Data literacy & Evidence building class by NYU/Accenture/UMD/KYStats/Coleridge Initiative

Anna-Carolina Haensch

No 4u6we, SocArXiv from Center for Open Science

Abstract: This document was written for participants of the DATA LITERACY & EVIDENCE BUILDING class by NYU/Accenture/UMD/KYStats/Coleridge Initiative, providing a focused overview of the synthetic data in the class. The instructors decided to use synthetic data for its accessibility and relevance. This document does not delve into the complexities of synthetic data, but rather, it recounts the key aspects that are important for participants when using synthetic data in class. This includes a comprehensive glossary of terms related to synthetic data and privacy, which will help participants navigate. In the following sections, we will summarize the focus of the class, as it helps in understanding the chosen dataset as well as the decision for synthetic data. We will then describe the data more in detail, beginning with an overview of the original data structure, sourced from the Kentucky Postsecondary Education Data System (KPEDS). We will then focus on our target sample, which comprises cohorts that commenced studying in Kentucky between 2013 and 2015, and a cross-sectional snapshot was taken in 2015. Subsequently, we will delve into the data preprocessing techniques implemented to clean and organize the dataset for the class. Lastly, we will discuss the synthetic data generation methods.

Date: 2023-07-31
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:4u6we

DOI: 10.31219/osf.io/4u6we

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