Coding qualitative data for non-researchers
Download as PPTX, PDF•2 likes•196 views
This document discusses qualitative and quantitative research methods. It explains that qualitative research deals with qualities and characteristics rather than numbers, and is used for gaining insights and discovering patterns and trends. Qualitative data works from the bottom up by generating codes and categories that emerge from the data, rather than testing a predetermined hypothesis. Grounded theory is mentioned, which aims to build theory from qualitative data through an iterative process of coding and analysis.
Coding qualitative data for non-researchers
- 1. Coding NPS Qualitative Data
- 3. What is qualitative data? It is qualitat
- 4. Quantitative research Observable and countable what people do, how often, how many, anything that is countable Can also ask for and count opinions Limited: know what and how, but not why
- 5. Quantitative research Hypothetical-deductive model Experimental reasoning Using statistical theory, you take a sample of a population Results can be generalized to an entire population (but NEVER absolute)
- 6. Qualitative research deals with qualities deals with nominal data Element of subjectivity and judgment Subjectivity of the analysis can be limiting Used for gaining insights & breakthroughs
- 7. Qualitative research Deductive nomological model Describes qualities and characteristics Good for discovery and insights Reveals values and motivations Looking for patterns and trends
- 8. Consider…. Why is the flagpole’s shadow twenty feet long? "Because that flagpole is 15 feet tall, the sun is at x angle, and because of the laws of electro- magnetism.” Why is the flagpole 15 feet tall?
- 10. Grounded theory Quantitative data works best from the top down Consider a survey or poll: we have a theory and a hypothesis. We know the range of answers Qualitative data works from bottom up Hypotheses – and theory – emerge from the data
- 11. Grounded theory Qualitative data works from bottom up Hypotheses – and theory – emerge from the data THUS – we are naming the data (nomological) we are applying labels (nomological)
- 12. Generating codes 1. Generate labels for the data 2. Don’t worry about the variety 3. Don’t worry about singletons or minorities 4. Codes aren’t always mutually exclusive, may be several codes 5. Anomalies may be just that OR may require further 6. Write notes to yourself, listing ideas or diagramming relationships you notice
- 13. Develop coding categories Use focused coding: process of eliminating, combining, subdividing Look for repeating ideas Repeating ideas: same idea expressed by different respondents Look for themes Theme: larger topic that organizes or connects a group of repeating ideas
- 15. For more research-based insights about our users, check out the UX insights portal: http://redacted.com Thoughts? Questions?