Data Analysis

Quantitative analysis uses data to answer policy questions. Analyzing survey data or administrative data, one can use descriptive techniques to characterize important trends or differences across subgroups, forecast future levels, or measure impacts of programs or policies. Microsimulation can answer “what if” policy questions about current data or future projected populations, and performance measurement techniques can provide real-time feedback on current policy and program operation.

Qualitative analysisis a continuous, iterative process of identifying patterns and building explanations that address the research questions. The goals of this process are to treat the evidence fairly, to produce compelling analytic conclusions, and to rule out alternative interpretations (Huberman, Miles, and Denizon 1994). The development of analytic files from site visit data begins with finalizing notes and team debriefings. Several tools, alone or in combination, can be used to reduce and analyze data, to visualize data across multiple sites and data sources, and to build testable explanations and theories about the research question at hand. These strategies help researchers to move beyond initial impressions to develop accurate and reliable findings.

 


Reference

Huberman, A. Michael, and Matthew B. Miles. 1994. “Data Management and Analysis Methods.” In Handbook of Qualitative Research, edited by Norman K. Denzin and Yvonna S. Lincoln, 428–44. Thousand Oaks, CA: Sage Publications.