Qualitative data analysis shares some similarities with quantitative data analysis. Both methods systematically summarize and compare data to obtain theoretical ideas from empirical data. There are key differences in the purpose and procedure of qualitative data analysis that distinguishes it from quantitative data analysis. The foundation of analyzing non-numeric data is finding meanings implied in the data. In-depth interviewing is perhaps the most widely used qualitative method. Transcribed interviews are treated as text data, similar to archival data or other document-type data. In quantitative analysis, the primary goal is to reduce data into numbers that can be manipulated and computed mathematically. Qualitative data coding can be done in a top-down fashion as well. Grounded theory methods develop a theory grounded in the data by way of a multi-level coding and summary procedure. An analytic summary requires comparing, generalizing, sequencing/ordering, and making inferences.
Stored only when both papers are in the corpus — 624 citations exist upstream.