Georgetown University Library Details Comprehensive Data Analysis Methods for Researchers
Georgetown University Library has outlined a comprehensive guide to data analysis methods, categorizing them into quantitative, qualitative, and mixed approaches. The guide emphasizes that data extends beyond traditional spreadsheets to include diverse materials such as photographs, field notes, interview transcripts, machine learning datasets, and laboratory observations. It further classifies analysis by purpose, including descriptive, exploratory, inferential, predictive, or causal analysis, noting that a project can embody multiple classifications, such as being both quantitative and descriptive. The library stresses that the choice of method should align with the research question, the type of data collected, the study design, and the intended claim, rather than being driven by software or statistical technique. Common statistical techniques mentioned include t-tests, analysis of variance, chi-square tests, correlation, and regression, with specific guidance on when to apply linear versus logistic reg...
