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Teaching Spatial Data Analysis: A Case Study with Recommendations

Author

Listed:
  • Mayer Duncan J.
  • Fischer Robert L.

    (Jack, Joseph & Morton Mandel School of Applied Social Sciences, Case Western Reserve University, 10900 Euclid Avenue, 44106-7078, Cleveland, OH, USA)

Abstract

Learning from data is a valuable skill for nonprofit professionals and researchers. Often, data have a spatial component, and data relevant to the nonprofit sector are no exception. Understanding spatial aspects of the nonprofit sector may provide immense value to social entrepreneurs, funders, and policy makers, by guiding programmatic decisions, facilitating resource allocation, and development policy. As a result, spatial thinking has become an essential component of critical thinking and decision making among nonprofit professionals. The goal of this case study is to support and encourage instruction of spatial data analysis and spatial thinking in nonprofit studies. The case study presents a local nonprofit data set, along with open data and code, to assist the instructors teaching spatial aspects of the nonprofit sector. Pedagogical approaches are discussed.

Suggested Citation

  • Mayer Duncan J. & Fischer Robert L., 2024. "Teaching Spatial Data Analysis: A Case Study with Recommendations," Nonprofit Policy Forum, De Gruyter, vol. 15(1), pages 71-82, January.
    • Handle: RePEc:bpj:nonpfo:v:15:y:2024:i:1:p:71-82:n:1
    DOI: 10.1515/npf-2022-0044
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    References listed on IDEAS

    as
    1. Jun Yan & Chao Guo & Laurie E. Paarlberg, 2014. "Are Nonprofit Antipoverty Organizations Located Where They Are Needed? A Spatial Analysis of the Greater Hartford Region," The American Statistician, Taylor & Francis Journals, vol. 68(4), pages 243-252, November.
    2. Leo van Wissen, 2004. "A Spatial Interpretation of the Density Dependence Model in Industrial Demography," Small Business Economics, Springer, vol. 22(3_4), pages 253-264, April.
    Full references (including those not matched with items on IDEAS)

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