Qualitative data analysis allows researchers to explore context, perceptions, attitudes, and experiences. It is a complex process that follows the traditions of the selected methodology. The researcher moves from individual data units to an interpretation that addresses the research question. The process involves understanding the inductive or deductive approach, analyzing experiences and perspectives, sorting codes into categories, identifying themes, and presenting findings with narratives, visuals, and quotations to explain themes and relationships in the data.

1. Analyzing Qualitative Data
Qualitative approaches allow you to:
explore and understand the context (social, economic, cultural, etc.)
investigate perceptions, attitudes and experiences
explore interactions between individuals / groups and a range of factors
This is only a basic guide. Qualitative data
analysis is a complex process and should
follow the traditions of your selected
methodology / researcher position. It should
always lead you to being able to address your
research question(s).
SP4021/29Quick Guide
Qualitative data analysis: A process in which the researcher moves from individual data
units to an interpretation that helps explain and understand phenomenon
Step 1
Understand your approach
Inductive - identifies themes from the 'bottom up' and makes links
between them
Deductive - starts with a theory or lens to explore the data and
identify relevant themes
Step 2
What are you analyzing?
Experiences, attitudes, perceptions. Temporal dimension, histories,
and how people see themselves and others. Why do people think that
way? How did they come to that view?
Step 4
Arrange the data - step 2
Sort codes into categories - groups of data (or codes) that provide
the building blocks of theory / explanation.
Step 5
Arrange the data - step 3
Identify main themes (super-ordinate) and subthemes (subordinate)
which link related groups of data and help bring clarity and
understanding
Step 6
Present your findings
Use a mix of narrative and visual presentation approaches including
tables, graphical representations, network maps, matrices (etc.) and
participant quotations. Explain the meaning of themes and
relationships between the data
Step 3
Arrange the data - step 1
Read your interview transcripts line-by-line. Identify 'codes' which
capture the essence of what is being said. Look for significant
statements and establish a coding list