Analysis of Data Qualitative Data Analysis Babbie & Mouton, 2005. The Practice of Social Research. Cape Town: Oxford

Qualitative Data Analysis See diagram of Renate Tesch p.490 NB is Tesch’s book – Qualitative research: Analysis types & software tools (1990) More than twenty approaches to qualitative data Following three is most common research interests: Characteristics of language Discovery of irregularities Comprehension of meaning of text/action

Characteristics of Language Two analytical approaches: Content Analysis Focuses on content characteristics Very much like quantitative analysis – useful in market research Divided into two types Conceptual/Thematic analysis – Comprises eight steps Relational analysis (Relationship between elements in data) – Comprises various steps Discourse Analysis Focuses on process characteristics Complex process & difficult to learn Parker proposes seven criteria for distinguishing discourses: Realizes in texts Is about objects Contains subjects Is coherent set of meanings Refers to other discourses Reflects its own way of speaking Is historically located

Content Analysis Conceptual/Thematic analysis – Comprises eight steps: Deciding the level of analysis (one word or a phrase) How many concepts to code for Whether to code for existence/frequency of a concept How to distinguish among concepts Developing rules for the coding of text What to do with irrelevant information Coding texts (making sense of the patterns & themes of the text Analyzing results

Content Analysis Relational analysis (Relationship between elements in data) – Comprises various steps such as: Id the question Choose the sample/s for analysis Determine the type of analysis Reduce text to categories & code for words or patterns Explore the strength, sign & direction of relationships Code the relationships Possibly perform statistical analysis Map out the representations

Research Interest: Discovery of Regularities Grounded Theory: Discovery of regularities as the id of categories of elements & establishment of their connections Inductively derived – discovered, developed & provisionally verified through systematic data collection & analysis of data pertaining to the research Begins with an area of study & what is relevant to that area is allowed to emerge An approach that allows us to study relatively unknown social phenomenon around which no theory exist Two main processes to grounded theory analysis: Coding procedures – open, axial & selective coding Adjunctive procedures – e.g. memos

Computer-aided Tools for Qualitative Data Analysis (CAQDAS) Following uses of a combination of various CAQDAS packages: Making notes in the filed & Writing up/transcribing field notes Editing: correcting, extending/revising field notes Coding: attaching key words/tags to segments of text to permit later retrieval Storage: keeping texts in an organized database Search & retrieval: locating relevant segments of text & making it available for inspection Data “linking”: connecting relevant data segments with each other, forming clusters/networks of info Meaning: writing reflective commentaries on aspects of data for deeper analysis Content analysis: counting frequencies, sequence/locations of words & phrases Data display: placing selected/reduced data in condensed, organized format e.g. matrix for inspection Conclusion drawing & verification: aiding the analyst to interpret displayed data & test/confirm findings Theory building: developing systematic conceptually coherent explanations of findings, creating diagrams/theories Preparing interim & final reports