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Methods of qualitative data analysis

Data is a source of great information which can enable informed decision making for businesses. Data is divided into Quantitative Data and Qualitative Data. Qualitative data refers to those non-numerical, explanatory data. Herein, we will have a detailed look into the various methods of qualitative data analysis.

What is Qualitative Data Analysis?

The process of Qualitative Data Analysis includes analysing information or data which aids in offering a certain level of understanding, explanation, and aids in interpreting the patterns and themes included in textual data. To put it in general words, qualitative data cannot be expressed in the form of numbers and is often represented in words, observations, pictures, and symbols.

Now coming to the methods used for analyzing qualitative data. There exist numerous methods for analyzing and interpreting qualitative data. However, the most popular and viable methods are listed below which includes 4 prominent techniques viz.

  1. Content Analysis
  2. Narrative Analysis
  3. Grounded Theory Analysis
  4. Framework Analysis
  5. Discourse Analysis

1.Content Analysis

This is the most popular type of qualitative analysis technique used by researchers. It primarily includes interpreting the meaning of data and identifying the important points in the content. It popularly includes analyzing the data published in the social media field so as to understand and interpret the current patterns and trend in social media.

Key purpose includes:

  • Finding the important aspects of social media content through emails, chats, comments, business emails, blogs, news, etc.
  • To present them in an effective manner.
  • The popular techniques under these are the conventional, summative and directive approach.

2. Narrative Analysis

This type of data analysis is used for interpreting different types of stories. It primarily aids in understanding how individuals form meanings in their lives so as to explain their day to day workings and world. A narrative analysis uses units like personal accounts, journals, autobiographical writing, letter writing, etc.

Key purposes include:

  • Aids in connecting past with the current situation.
  • Understanding the interpretation of events.
  • Gain knowledge about people, their culture and changes happening.

3. Grounded Theory Analysis

This method involves the generation of theory through the collection of data and its analysis. The primary feature of this analysis is that it helps in focusing on theory development. They are useful in interpreting a large quantity of data involving a large unstructured group. The key methods include:

  • Interpretation of texts
  • Focus groups
  • Interview with open-ended questions
  • Participant observation

4. Framework Analysis

This type of data analysis method is used to manage and organize information using the process of summarization. As the meaning of the word framework goes, it helps in categorizing the data into a matrix comprising of rows (cases) and columns (codes) and cells of summarized data.

Use:

  • Helps in identifying similarities and differences in qualitative data
  • Aids in drawing descriptive and explanatory conclusions

5. Discourse Analysis

It is widely in the field of linguistics that lays focus on the role of language in building social reality. It thus deals with interpreting language through communication and different types of texts.

Use:

  • Helps in exploring different texts, discourses, and its context
  • Aids in drawing inferences

Choosing the appropriate qualitative data analysis technique will help achieve the desired result along with gaining a deeper understanding of the data, its explanation and interpretation.

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