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Qualitative Data Interpretation
                   It is the process of analysing and understanding non-numeric data. This type of data is unstructured and often
                 comes from interviews, surveys, observations, or textual content. Qualitative data tells us about the emotions
                 and feelings of people. Qualitative data interpretation is focused on insights and motivations of people.


                 Data Collection Methods in Qualitative Data Interpretation
                 Data collection methods in qualitative data interpretation involve techniques such as interviews and observations
                 to  gather  rich,  descriptive  data  for  detailed  analysis,  fostering  a  deeper  understanding  of  complex  human
                 experiences and behaviours. Some methods are as follows:

                    • Record keeping: This method utilises documents that are reliable and well curated and other similar sources of
                   information as the data source that are verified and maintained. It is similar to going to a library.
                    • Observation: In this method, data is collected by observing the participants, their behaviour and emotions,
                   carefully.
                    • Case studies: In this method, data is collected from case studies.
                    • Focus groups: In this method, data is collected after a group discussion on topics of relevance.
                    •  Longitudinal studies: In this data collection method, data is collected on the same data source repeatedly over
                   an extended period of time.
                    • One-to-one interviews: In this method, data is collected using a one-to-one interview.


                 Open Ended Surveys and Questionnaires

                 Open ended surveys and questionnaires allow organisations to collect views and opinions from respondents
                 without meeting in person.

                 Steps to Qualitative Data Analysis

                 The five steps involved in qualitative data analysis are:
                 1.   Collect data: Gather qualitative data through various methods to understand people’s experiences, opinions,
                    or behaviours. This is done through interviews, surveys, observations, or documents. For example, a researcher
                    interviews patients about their experiences with a new healthcare app, recording their responses for further
                    analysis.
                 2.   Organise and connect the qualitative data: Prepare and arrange the collected data in a systematic way
                    to make it easier to work with. For example, the researcher transcribes the recorded interviews into text
                    documents and organises them by participant or interview date.
                 3.   Set a code to the data collected:  Assign  labels  or  codes  to  different  parts  of  the  data  to  identify
                    themes, patterns, or categories. For example, the researcher reads through the interview transcripts and
                    highlights sections discussing "ease of use," "technical issues," and "benefits of the app," tagging them with
                    corresponding codes.
                 4.   Analyse your data for insights: Examine the coded data to identify deeper patterns, relationships, and
                    insights. For example, The researcher groups codes related to "ease of use" and "technical issues" into a
                    broader theme of "user experience" and analyses how these themes impact overall user satisfaction with the
                    app.
                 5.   Reporting on insights derived from analysis: Present the findings clearly, using quotes and visual aids to
                    support your conclusions and recommendations. For example, the researcher writes a report highlighting
                    the main themes along with positive and negative feedback.


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