There is a significant difference between qualitative and quantitative data analysis. Qualitative data is consists of words and often considered rich and subjective. It gives in-depth information presented in the form of words. Qualitative data analysis finds the differences and similarities, and finds subsequent themes and then develops categories. The use of software has made the categorization of qualitative data very easy and reduced the technical sophistication and laborious work of the researchers. Including SPSS, in recent times there are a number of software packages that help in the coding process of qualitative data analysis.
Qualitative research methods explore the social structures, meaning, and perspective of experiences and processes that explain and interpret the peoples’ behaviors. Qualitative research is based on interaction with the subjects being studied that allows discovering the unanticipated information. The qualitative research method is useful in the fields of health and education, for example, better policies can be developed if people behaviors are clearly understood.
Steps in qualitative data analysis
Data analysis in qualitative research involves a number of steps. Following are the steps in qualitative data analysis:
1. Selection of a relevant qualitative research method
Qualitative data is non-numeric information such as texts document, notes, videos, audios, and images, etc. Qualitative data can be analyzed in one of the following categories:
1. Discourse analysis: In this method, the researchers discuss all types of naturally occurring talks and discourses.
2. Case Study Model: This method looks into a single case in-depth to explain and describe it more comprehensively.
3. Content analysis: content analysis is the type of qualitative research analysis in which the verbal and behavioral data is classified, summarized and tabulated.
4. Focus group discussions: In this method, different people are interviewed in groups to know their perceptions regarding a specific problem or a situation.
5. Ethnographic Model: The ethnographic model is used to know the characteristics of an unfamiliar culture.
6. Narrative Model: The narrative model is, in fact, the revision of primary data collected from the respondents. The researcher reformulates the stories narrated by respondents with respect to the context of each story presented.
7. Framework analysis: Framework analysis consists of multiple stages such as familiarization with the qualitative data, coding, identifying the themes, charting, mapping and at the end interpretation of qualitative data.
8. Grounded Theory Method: This method discusses a single case study in-depth to formulate a theory. Then, related case studies are examined to know if they contribute to the developed theory.
9. Historical Model: Historical method is used to interpret past events to understand the present and future anticipated events.
10. Phenomenological Method: This qualitative research method is applied to know how a particular person feels about a specific problem or phenomenon.
2. Coding and categorization of data
After selecting the appropriate qualitative research method the next step is coding and categorization of qualitative data. Coding may be described as the categorization of qualitative data. A “code” can be a single word or phrase that represents a coherent theme or idea. After coding all these codes are assigned meaningful titles. A wide range of qualitative data such as events, activities, meanings, and behaviors can be coded. The quantitative research process does not need such type of coding instead it applies statistical methods to analyze data.
Three types of coding
The following are three steps of the coding process for qualitative data analysis.
1. Open coding: The initial meaningful arrangement of data is called open coding.
2. Axial coding: After a meaningful arrangement of the data the codes and categories are linked together.
3. Selective coding: After interlinking, the relevant codes and categories researcher formulates a story and interprets the data.
This coding may be done manually or by the use of computer applications as required by the nature of data and study.
a. Manual coding
Although manual coding takes too much time and effort but its results are more satisfactory than the computer-based coding. Researchers use different physical folders, wallets, and cabinets to gather materials.
b. Computer-based coding
In the computer-based coding the physical wallets, folders, and cabinets are replaced with computer folders and files. There are different software available for qualitative data analysis such as Atlas ti 6.0, NVivo, Max QDA, HyperRESEARCH 2.8 and others. While choosing the software for qualitative data analysis research should consider a range of factors such as:
1. Type and amount of qualitative data
2. The time required for the analysis
3. Cost of software
4. The time required mastering the software
5. Identification of themes and patterns
Unlike quantitative research methods, qualitative data analysis does not apply universal techniques to generate results. The researcher’s critical and analytical thinking plays an important role in qualitative data analysis studies. Therefore, qualitative analysis cannot be repeated to produce the same results.
However, there is a set of techniques to analyze the qualitative data which includes identification of common themes and patterns. And researcher builds relationships within responses of samples on the basis of identified themes and patterns.
Data analysis in qualitative research have the most common and popular data interpretation techniques:
1. Repeated words and phrases
2. Researchers scan the qualitative data to find the most commonly used words and phrases by the respondents. Researchers also try to find the words and phrases with specific or unusual emotions.
3. Primary and secondary data comparison
4. Researchers compare the primary and secondary data to discuss the differences between them. Primary data includes the findings of the focus group, interview, questionnaire, observation and other qualitative methods of data collection. Secondary data include the findings of the literature review. Researchers find differences between the findings of primary data and secondary data.
5. Looking for missing information
6. Researchers point out which aspects of the study were not mentioned and discussed by the respondents. Researchers try to find the gaps and silences in the collected data.
7. Comparing with analogous study
8. Researchers compare the research findings of the study to the other phenomena with the same objectives to discuss the differences and similarities.
9. Summarizing the qualitative data
10. At this last step, researchers link the findings of the study with the hypotheses, research questions and research objectives of the study.