Increasing Interest in Data Literacy: The Quantitative Public Health Data Literacy Training Program

Jinal Shah, Jemar R. Bather, Yuyu Chen, Sumedh Kaul, Janice Johnson Dias, Melody S. Goodman

Research output: Contribution to journalArticlepeer-review


Due to the COVID-19 pandemic, the presentation of public health data to lay audiences has increased without most people having the knowledge to understand what these statistics mean. Recognizing that minoritized populations are deeply impacted by the pandemic and wanting to improve the racial representation in biostatistics we developed a training program aimed at increasing the data literacy of high school and college students from minoritized groups. The program introduced the basics of public health, data literacy, statistical software, descriptive statistics, and data ethics. The instructors taught eight synchronous sessions consisting of lectures and experiential group exercises. Five of the sessions were also offered asynchronously. Of the 209 students, 76% were college students; 90% identified as Black, Asian, or Latino/a/x; and the average age was 21 years. In synchronous sessions, 56% of students attended all sessions. All course sessions were rated as good/excellent by most ((Formula presented.)) students. The program recruited, engaged, and retained a large cohort ((Formula presented.)) of underrepresented students in biostatistics/data science for a virtual data literacy training. The program demonstrates the feasibility of developing and implementing public health training programs designed to increase racial and gender diversity in the field.

Original languageEnglish (US)
JournalJournal of Statistics and Data Science Education
StateAccepted/In press - 2024


  • Data ethics
  • Data visualization
  • Diversity, equity and inclusion
  • Statistical software
  • Web training

ASJC Scopus subject areas

  • Statistics and Probability
  • Education
  • Management Science and Operations Research


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