LISA 2020 Network Survey on Challenges and Opportunities for Statistical Practice and Collaboration in Developing Countries

• Published in: Promoting Statistical Practice and Collaboration in Developing Countries pp. 47 - 59
• Main Authors: Love, Kim, Awe, O. Olawale, Gunderman, David J., Druckenmiller, Matthew, Vance, Eric A.
• Format: Book Chapter
• Language: English
• Published: CRC Press 2022
• Edition: 1
• Subjects: SCS; Undergraduate Statistics Programs; Exponential Ratio Type Estimator; Statistical Practice; Lowest Average Response; Local Development; Vice Versa; Statistical Laboratory; HPD Interval; Statistical Challenges; Data Science Practice; Bachelor's Students; Member Stat Labs; Development Policy Actors; Individual Stat Labs; Pennsylvania State University; Statistical Computing; Statistical Consulting Centers; Developmental Challenges; Likert Type Items; General Statistical Practice; Statistical Literacy; Data Science Skills; Statistical Collaboration; Undergraduate Statistics Students; Domain Experts; Autoregressive Distributed Lag Model; HPD
• ISBN: 103219555X; 9781032195551; 1032198508; 9781032198507
• DOI: 10.1201/9781003261148-4

The LISA 2020 program trains local statisticians and data scientists in developing countries to collaborate with researchers, businesses, and policymakers. This article analyzes a voluntary survey that was provided to all members of the LISA 2020 Network in August of 2020. The purpose of this survey was to gain an understanding of the environment surrounding statistical practice and collaboration in the developing countries where the network operates. Results indicate that many LISA 2020 Network stat lab staff members have extensive education and experience with statistical practice, but relatively less experience with statistical collaboration. With regard to statistical practice, the areas of greatest concern for the respondents include access to computing resources and overall statistical literacy within society; with regard to statistical collaboration specifically, the areas of greatest concern include expanding training in statistical collaboration and increasing the funding that is available to support this collaboration. Based on the challenges and ways to improve statistical practice and collaboration suggested by this survey, we identify priorities for the LISA 2020 Network.