Data Analysis
Data analysis is the process of organising, interpreting, and examining collected data in order to answer research questions and achieve research objectives. It involves identifying patterns, relationships, and insights from qualitative or quantitative data.
On this page:
- What is Data Analysis?
- Qualitative vs Quantitative Data Analysis
- When to Discuss Data Analysis
| Aspect | Qualitative Data Analysis | Quantitative Data Analysis |
|---|---|---|
| Data type | Text, images, observations | Numbers, measurements |
| Approach | Interpretative | Statistical |
| Goal | Understand meanings | Test relationships |
| Techniques | Thematic analysis, coding | Descriptive & inferential statistics |
| Output | Themes, insights | Tables, charts, models |
Qualitative vs quantitative data analysis at a glance
Qualitative analysis explains meaning, whereas quantitative analysis measures relationships.
What is Data Analysis?
Data analysis means:
- Organising your data
- Identifying patterns and trends
- Interpreting what the data means
It answers the question:
“What do the results show?”
Methodology chapter of your dissertation should include discussions about the methods of data analysis. You have to explain in a brief manner how you are going to analyze the primary data you will collect employing the methods explained in this chapter.
Qualitative vs Quantitative Data Analysis
There are differences between qualitative data analysis and quantitative data analysis. In qualitative researches using interviews, focus groups, experiments etc. data analysis is going to involve identifying common patterns within the responses and critically analyzing them in order to achieve research aims and objectives.
Data analysis for quantitative studies, on the other hand, involves critical analysis and interpretation of figures and numbers, and attempts to find rationale behind the emergence of main findings. Comparisons of primary research findings to the findings of the literature review are critically important for both types of studies – qualitative and quantitative.
Data analysis methods in the absence of primary data collection can involve discussing common patterns, as well as, controversies within secondary data directly related to the research area.
When to Discuss Data Analysis
Data analysis should be clearly explained in the methodology chapter, before presenting findings.
You should:
- Specify the techniques you will use
- Justify why they are appropriate
- Link them to your research objectives
- Ensure consistency with your research approach
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John Dudovskiy