Qualitative data analysis is dependent on research using various approaches in collecting data. Qualitative research techniques are used to create insights about situations or problems where we would like to have more knowledge. There are several qualitative techniques that are used to gather the qualitative data necessary to do qualitative market research or statistical studies. These research techniques can range from loosely structured interviews that contain open-ended questions to conducting focus-group discussions with participatory approaches.
Research and data gathering first needs to be completed before a statistical consultant can start any step towards data analysis or before data can be used in a database management system. Preparing the data for analysis is the first step you need to take before conducting qualitative data analysis. This is where an inventory of all the data gathered is reviewed and sorted for quality and relevance to the study.
Once data entry has been completed and the data has been sorted, the variables are summarized into qualitative data that should make it easy to analyze. The summarized data are written into charts, diagrams, matrices and narratives that will help in forming new variables. These can then help determine any associations that may be formed between the variables. All these are prepared before all the data is subjected to statistical analysis.
In collecting data, the most common tool used when collecting qualitative data is an open questioning technique. Specifically designed questions are used, and the answers are loosely organized based on the type of answers byisting all the answers first and then organizing them based on how similar they are to each other in relation to the question that were asked. Oftentimes, the narratives are filled with other data that are not related to the question asked and so do not come out in the data to be analyzed. Because of this, it is also important that the narratives are arranged according to how relevant it is to the situation being analyzed.
Summarizing data in compilation sheets is needed before any test, like a logistical regression analysis, is to be conducted. Similar to quantitative data, these compilation sheets composed of qualitative data have columns of data based on study headings. These may be further broken down into various related themes. All this qualitative data can then be further summarized into matrices, tables and figures to make it possible to compare all the variables. Matrices are charts similar to those used for quantitative data, but these may also contain descriptive words aside from numbers. These matrices may make it easier for the researchers to form conclusions.
If researchers are able to form and verify their conclusions based on qualitative data analysis, then the project can be deemed a success. However, forming conclusions does not only come at the end of the whole activity. These conclusions and summaries may change as all the qualitative data is being studied. Gathering, studying, analyzing and summarizing qualitative data is all part of an intertwined process that is necessary in qualitative data analysis.