Qualitative Data Analysis– Analysis based on Interpretative Philosophy

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Data can also be Qualitative?

We always hear about quantitative data, data which consists of figures and numbers, those that can be measured and used in calculations. But there is also something called qualitative data – a form of nonnumeric data collected from sources such as audio recordings, texts, observations, documents, and reports. Such data usually involve activities, conversations, and interpretations of people.

As with all data, qualitative data also can be analyzed and interpreted for better understanding. Qualitative analysis transforms data into findings and there is no fixed formula for the transformation. There is some guidance and directions, but the final interpretation and analysis lies with the inquirer.

What is Qualitative Data Analysis?

Qualitative Data Analysis (QDA) is the range of processes and procedures used on the qualitative data that have been collected to transform them into some form of explanation, understanding or interpretation of the people and situations that are being investigated.
QDA is usually based on an interpretative philosophy. The intention behind qualitative analysis is to answer the ‘why’, ‘what’ and ‘how’ questions, and to examine the meaningful and symbolic content of qualitative data.

For example, students doing research and fact findings about increase in obesity among young children may ponder on the following queries and tasks:

  • How and why are the food habits of young children changing?
  • Are more children consuming fatty, fast foods? If so, what are the reasons behind this trend?
  • Is financial status and education of family members related to food habits and diet plans?
  • Interview school children on their daily food intake and habits.
  • Observe the levels of awareness on healthy eating and means of spreading the awareness.
  • List the problems the participants face while trying to comply with a healthier food habit.

Drawing inferences on the basis of interviews, observations, and analysis of the real life experiences of a sample group of children will be part of the qualitative analysis process.

Process of QDA

The process of QDA mainly involves the following procedures or steps:

  • Creating content and categorizing them into Themes:
    The initial step is to write down all observations, facts, and approaches for all your findings. All audio recordings should be transcribed and findings from surveys and reports should be noted down. Next step is to categorize and organize all the textual content along with the images, videos, and other factual data gathered during the research process. After categorizing they should be labeled so that it is easy to retrieve and examine data under a particular thematic idea. As there may be vast amount of data, it is important to be organized in sorting and storing the data.
  • Interpretation and Authentication of data:
    The inferences and results from the qualitative data will lie in the proper interpretation of collected data. Before interpreting, the data should also be analyzed for its authenticity.
  • Methodology to be followed for Qualitative Data Analysis:
    There are several approaches for qualitative data analysis. One of the important models developed by Seidel in 1998 consists of three sections of Noticing, Collecting and Thinking, which are considered to be interlinked and cyclical.

Conclusion

Qualitative data analysis plays an important role in research. Qualitative research is interesting because you analyze the facts that lie behind the collected information and interpret your findings on the basis of that. You use this type of analysis to find out how and why things happen, which is a tricky part of any research process.

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