This article introduces the foundational principles of data analysis for non-profits, focusing on data types, collection methods, and key statistical tools. It explains the role of qualitative and quantitative data, outlines practical methods such as surveys, interviews, focus groups, observation, and document review, and stresses the importance of data quality through accuracy, reliability, and validity. Basic statistical concepts—including mean, median, mode, standard deviation, and correlation—are presented as accessible tools for non-profit practitioners. Case illustrations from health, education, and fundraising contexts show how these principles can be applied in practice to strengthen transparency, accountability, and evidence-based strategies.
Anna Neya Kazanskaia (Wed,) studied this question.