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
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