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The second part, theory analysis, is the process of interpreting your data. You can employ a variety of analytic methods to make sense of the data that you have taken in, including qualitative and quality methods.

Based on the type of assessment you are undertaking depending on the type of analysis you are conducting, you may need to identify repeating themes and patterns within your data or look for connections between different items. Analysis involves coding, sorting and comparating data with theories and concepts. It also involves making sense of the information you find in your data.

For instance, when conducting an analysis of the participants in a program you can employ the theory of grounded theory (GT) to guide the analysis process and to help develop an idea of the theoretical basis from your data. GT is an inductive research methodology that lets you discover new theories by constantly interplay between data collection and analysis. The GT method generally involves open coding in order to discover interesting phenomena in the data; axial coding to identify the connections between phenomena and also selective coding in which you select a central concept to keep the ideas that are emerging together.

The primary category is an amalgamation of all the emerging phenomena. It could be an individual concept or a set of related concepts. The chosen idea is compared to a theory, and fit is assessed through repeated comparisons of events to the selected concept. During this phase, memos are kept to record and think about the emerging ideas.