ABSTRACT
In practice, conducting a systematic and scientifically sound qualitative analysis can be quite difficult. The analysis of qualitative data may even impose higher demands on the researcher, as it requires a great capacity for logical reasoning and the ability to oversee a large body of data. Qualitative data are non-numerical units of information, for example statements, text or interview fragments and images (photos, posters). Usually, qualitative data are unstructured and cannot be arranged hierarchically – contrary to quantitative data, for which the readers can distinguish different levels of measurement. Moreover, qualitative data are often hard to circumscribe. In a nutshell, the analysis of qualitative data consists of dividing the data units into even smaller units, labelling these units with a code and comparing the different codes with each other. This process is often one of trial and error, which places great demands on the researcher in terms of creativity and logical thinking.
