Defining and Distinguishing

• Qualitative Data refers to data that is not numerical and typically relates to concepts, opinions or experiences.
• On the other hand, Quantitative Data is numerical and can be measured or quantified.
• Qualitative data is often described as unstructured because it cannot be neatly fit into stats or mathematical models.
• Conversely, quantitative data is structured; it can be organised and analysed using statistical methods.

Gathering Data

• Gathering qualitative data often involves methods such as interviews, focus groups, and participant observation, which aim to gain a detailed understanding of a topic.
• Quantitative data is commonly collected through methods such as surveys or experiments which produce numerical results.
• While collecting qualitative data, the main aim is to get an in-depth comprehension of human behaviour and the reasons behind such behaviour.
• While collecting quantitative data, the objective is to generate numerical data that can be transformed into usable statistics.

Analysing and Interpreting Data

• Qualitative data analysis is frequently interpretive and seeks to explain the 'why' and 'how' of human behaviour.
• Quantitative data analysis, however, often involves focusing on the measurable, using methods such as statistical analysis or computational techniques.
• Qualitative data lends itself to detailed, narrative descriptions, while quantitative data results in numerical summaries, charts, or graphs.
• Interpretations of qualitative data are based on observed patterns or themes, while quantitative data interpretations rely on statistical significance or differences in measurement.

Strengths and Weaknesses

• Qualitative data can provide rich, detailed information but may be difficult to generalise and time-consuming to collect and analyse.
• Quantitative data, however, is relatively quick to collect and analyse and can be easily generalised but may not provide the same depth or complexity of information.
• It's worth noting that combining both qualitative and quantitative data, a method known as 'mixed methods' approach, can leverage the strengths of both, helping to build a more complete and nuanced understanding of the study area.