Analyzing qualitative data

Both quantitative and qualitative data analysis involves inference. Researchers infer from the empirical evidence of social life. To infer means to pass a judgment, to use reasoning, and to reach a conclusion based on evidence.

In qualitative research, adequacy of data means the amount of data collected, rather than to the number of subjects as in quantitative research.

In both methods, the researchers systematically record and gather data and in so doing making accessible to others what they did. They all look for patterns- similarities and differences. Qualitative researchers examine the similarities and differences across cases and try to come to terms with their diversity, quantitative researchers examines differences across the cases in order to explain the covariation of one variable with another, usually across many cases.

For qualitative research, the data analysis is less a distinct final stage of research than a dimension of research that stretches across all stages.

The qualitative researchers analyze data by organizing it into categories on the basis of themes, concepts, or similar features. Then develop new concept, formulate conceptual definitions. Idea and evidence are interdependent.

Coding data:

Codes are tags or labels for assigning units of meaning to he descriptive or inferential information complies during a study. Coding involves mechanical data reduction and analytic categorization of data.

Open coding: is performed during a first pass through recently collected data. The researcher locates themes and assign initial codes or labels in a first attempt to condense the mass of data into categories.

Open coding brings themes to the surface from deep inside the data.

Axial coding:This is second stage passing through the data. The researcher begins with an organized set of initial codes or preliminary concepts, he focuses on the initial coded themes more than on the data. Additional codes or new ideas may emerge during this pass and the research notes them. He then moves toward organizing ideas or themes and identifies the axis of key concepts in analysis.

Axial coding stimulates thinking about linkage between concepts or themes, and it raises new question, it reinforce the connection between themes and evidence.

Selective coding: The last phrase of passing through the data, he has identified the major themes of the research project, selective coding involves scanning data and previous codes. Then he looks selectively for cases that illustrate themes and make comparisons and contrasts after most of all data collection is complete.

They begin after they have well developed concepts and have started to organize their overall analysis around several core generalizations or ideas. The major themes and concept ultimately guide the researcher's project. Finally reorganizes the specific themes identified in earlier coding and elaborates more than one major themes.