Quantitative analysis techniques
Raw numerical data need to be processed and analysed to make them meaningful. Quantitative analysis techniques include tables, graphs and statistics (Saunders, Lewis and Thornhill 2015, p496).
Establish patterns and relationships
The way you present your data will help identify patterns and relationships in your research. These can be (depending on the field/subject) (Cottrell, 2014, p173):
In qualitative research, meanings are derived from words and images - not numbers, as in quantitative research. Words and images can have multiple meanings, and need to be interpreted with care (Saunders, Lewis and Thornhill 2015, p568). For more information about qualitative data see the section on Methodology.
How to undertake qualitative data analysis:
Approaches to analysing qualitative data
Qualitative data analysis can take place using specific methods such as (there are many more, depending on your field!) thematic analysis, content analysis, grounded theory, narrative analysis, discourse analysis (see link below).
The most generic approach to qualitative data analysis is thematic analysis, whose purpose is to identify patterns in qualitative data (interviews, observations, documents etc.) (Saunders, Lewis and Thornhill 2015, p579). Thematic analysis can be inductive, deductive or hybrid:
Braun, V. and Clarke, V. (2006). Using thematic analysis in psychology, Qualitative Research in Psychology, 3(2), 77-101, DOI: 10.1191/1478088706qp063oa
Fereday, J., & Muir-Cochrane, E. (2006). Demonstrating Rigor Using Thematic Analysis: A Hybrid Approach of Inductive and Deductive Coding and Theme Development. International Journal of Qualitative Methods, 5(1), 80–92. https://doi.org/10.1177/160940690600500107