Qualitative data are data representing information and concepts that are not represented by numbers. They are often gathered from interviews and focus groups, personal diaries and lab notebooks, maps, photographs, and other printed materials or observations. Qualitative data are distinguished from quantitative data, which focus primarily on data that can be represented with numbers.
Qualitative data can be analyzed in multiple ways. One common method is data coding, which refers to the process of transforming the raw collected data into a set of meaningful categories that describe essential concepts of the data. Qualitative data and methods may be used more frequently in humanities or social science research and may be collected in descriptive studies.
(From the Data Glossary, National Center for Data Services, National Library of Medicine)
Below are some methods texts recommended by qualitative workshop leaders from the UC Berkeley Library and the D-Lab:
Unfortunately, Berkeley does not yet have a sitewide license for any qualitative analysis software.
If you are a student, you can find affordable student licenses with a web search.
If you are a faculty member, instructor, lecturer, or visiting scholar without grant funding, unfortunately software is quite expensive.
You can find reviews of many qualitative software packages at this University of Surrey link:
You can also check out the websites of several major options below:
Interpretations related to mixed (sometimes called merged) methods vary; be wary of jargon! Gery Ryan, of the Kaiser Permanente School of Medicine, gives these definitions, while arguing that we should be thinking of the purposes of the research rather than the methodological labels:
Mixed methods research: “Combines elements of qualitative and quantitative research approaches (e. g., use of qualitative and quantitative viewpoints, data collection, analysis, inference techniques) for the broad purposes of breadth and depth of understanding and corroboration.”
Multimethod research: “Either solely combine multiple qualitative approaches or solely combine multiple quantitative approaches.”
Data triangulation: “Uses multiple sources of data or multiple approaches to analyzing data to enhance the credibility of a research study.”
(From "Mixed Methods Research Designs and Data Triangulation" by Gery Ryan, Kaiser Permanente School of Medicine)