Data Analysis
Qualitative data analysis contains reviewing, summarizing, generalizing and interpreting data in an appropriate and accurate way. It is to describe and explain the phenomena or social worlds being studied. One of the most important steps in the qualitative research process is analysis of data. Analyzing qualitative data also requires researchers’ patience. There are two different analytical procedures: Meaning and discovery-Focused approaches. Meaning-focused approaches emphasize meaning comprehension. In other words, try to understand the subjective meaning of experiences for the participants, instead of placing those meanings into researchers’ own conceptions. Discovery-focused techniques aim to establish patterns and connections among elements of data. However, no matter which procedure is used, it is essential to apply an effective system for retrieving data because of the identity of qualitative data analysis, which is exploring data progressively.
There are also a variety of the available analysis tools and strategies for qualitative data analysis.
- Constant Comparison Analysis, or called "coding system" : Coding enables the researcher to locate and bring together similarly labelled data for examination and to retrieve data related to more than one label when wanting to consider patterns, connections, or distinctions between them.
- Keywords-in-Context: It is a data analysis method that reveals how respondents use words in context by comparing words that appear before and after "key words. KWIC is a helpful analysis to utilize when there are specific words that are of interest to the researcher or when the data appear to be less rich in information.
- Word Count: Word counts are based on the belief that all people have distinctive vocabulary and word usage patterns.
- Classical Content Analysis: Classical content analysis is similar to constant comparison analysis and also is used frequently in qualitative research.
- Domain Analysis: Domain analysis represents a search for the larger units of cultural knowledge, which Spradley (1979) called domains. This method of analysis stems from the belief that symbols are an important way of communicating cultural meaning. This analysis should be used when researchers are interested in understanding relationships among concepts.
- Taxonomic Analysis: Taxonomic analysis is the second step after domain analysis. This analysis helps the researcher to understand how participants are using specific words.
- Componential Analysis: Componential analysis is another step that can be undertaken after domains are created. It is used when a researcher is trying to uncover relationships between words.
Read more about this topic: Qualitative Psychological Research
Famous quotes containing the words data and/or analysis:
“To write it, it took three months; to conceive it three minutes; to collect the data in it—all my life.”
—F. Scott Fitzgerald (1896–1940)
“Analysis as an instrument of enlightenment and civilization is good, in so far as it shatters absurd convictions, acts as a solvent upon natural prejudices, and undermines authority; good, in other words, in that it sets free, refines, humanizes, makes slaves ripe for freedom. But it is bad, very bad, in so far as it stands in the way of action, cannot shape the vital forces, maims life at its roots. Analysis can be a very unappetizing affair, as much so as death.”
—Thomas Mann (1875–1955)