1. Qualitative analysis
Research methodology

2. Differences between qualitative and quantitative data
Transcribing qualitative data: reproducing the original data (eg.: audio recording) verbatim as a word processed account. Additional contextual information must be included.

3. The nature of qualitative analysis
Analyzing qualitative data without quantification (Quantified qualitative data can be analyzed in the same way as originally quantitative data). It is a non-numeric analysis.
Its philosophical background is interpretivism and social constructivism.
Quantitative analysis keeps closer to theory and research aims than quantitative analysis, because it is less mechanical and technical.

4. Revealing relationships
Frequency (of a given phenomenon).
Intensity or strentgh of the phenomenon.
Structure: types and relationships between the types
Patterns
Causes
Consequences (short term and long term)

5. Cross-case analysis Variable-oriented: Case-oriented
General consequences
Will not reveal all the factors about a given case
Case-oriented
Aims full understanding about a given case
Will not lead to any generalizable result

6. Grounded theory method
Purely inductive: builds on observations not on theories
No preconceptions
Steps:
Frequencies per categories
Integration of categories and their attributes
Circumscribing the theory: limitations
Writing out the theory

7. Semiotics Studies signs and symbols.
Signs, symbols has no meaning on their own, it is created by the society and depends on the context.
One symbol can bear multiple potential meanings.
Further reading:
American Journal of Semiotics; Punctum;
Lawes R. (2018) Science and semiotics: What’s the relationship? International Journal of Market Research. 60(6): doi: /

8. Conversational analysis
Analysing human conversations.
Nuances of the conversations has important meanings.

9. Coding The basic technique in qualitative analysis
Searching for categories (e.g. themes) and patterns occurring across the data set
Sources and types of codes:
Theory driven coding: a priory codes
Data driven coding (open coding):
Derived from data by the researcher
Actual terms used by the participants
The unit of analysis is a theme or notion
One unit can get more than one codes
Can be used for quantification, too
The ultimate aim of coding is understanding

10. Aids you can use in qualitative analysis
Memos or summaries:
Progress summaries
Transcript summaries
Document summaries
Self-memos
Research notebook
The envelope method
Concept-mapping

11. An example of a concept-map
Source: Babbie 2016