Sparsely populated rural areas are susceptible to high levels of error in their data, making it difficult to examine patterns and trends across geographies. This article aims to advance research methods for rural researchers by offering guidelines for navigating high levels of error associated with the American Community Survey (ACS). The ACS presents a useful source of U.S. community level data for rural researchers to utilize in school–community research but not without its difficulties. The small population sizes of rural communities often translate to large margins of error in the data, presenting a degree of uncertainty in the actual measure. To illustrate challenges and best practice, the author conducts a case study of the relationship between the presence of schools and economic vitality of rural communities in Indiana using ACS data. The author demonstrates how to examine the error in the data, introduces options to reduce uncertainty, and ultimately, explains how to move forward with the data, working with the margin of error and acknowledging its presence in the analysis and results. This article offers suggestions and techniques to assist rural researchers in navigating ACS obstacles so that they might produce transparent results with as little uncertainty as possible.

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