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Data processing and analysis. Ethical considerations. Quantitative Qualitative data
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Data processing and analysis
Quantitative and qualitative data have particular characteristics in the approach taken, the form the data takes and the analysis methods used. You might plan to use mixed methods, that is, a combination of both quantitative and qualitative approaches. And, if you have chosen mixed methods, you will need to be confident about delivering data processing and analysis on both quantitative and qualitative data. Some data, particularly secondary data produced by others, may need a lesser form of analysis than, say, primary data. Primary data collected by you will definitely need to be ana- lysed and it is important from the outset that you make yourself aware of the analytical facilities available to you. Quantitative data analysis can involve inputting the data into a spreadsheet or an IT statistical package that will allow for calculations and their pres- entation in the form of tables and charts. Qualitative data is undertaken in a different way. Although there are IT packages that can help in the analysis of qualitative data such as NVivo, ATLAS. ti, Quirkos or Provalis, many students analyse qualitative data derived from interviews or observations by identifying themes, patterns and trends, and then illustrating them with quotations drawn from the transcripts or field notes.
Thinking about how you will analyse the data, whether you actually have the
knowledge and skills to do it, what you need to learn in order to do it, and how long it will take are four key considerations that you will need to reflect on as part of the planning of your research project, making connections between what you want to do and how you will do it. Box 2. 8 provides detail on approaches to data analysis.
Ethical considerations
As David Scott details in Chapter 6 of this book, ethical considerations are an essen- tial ingredient in planning your research project and require careful thought,
BOX 2. 8 APPROACHES TO DATA ANALYSIS
Quantitative Qualitative data
In taking a quantitative approach, you will know in advance what you are looking for (hypothesis), you will try to remain objective and distinct from the focus of the research and will use the data to count, classify or construct statistical models to explain your observations.
What does the data look like and how is it explored and analysed?
Data:
· Numbers and statistics
· Efficient in testing hypothesis
• Misses contextual detail
Exploring the data:
· graphs and charts
· cross-tabulations
• seeking patterns and relationships in the data
• comparing means, exploring correlations.
Steps in analysis method:
1. Identifying a data entry and analysis manager (e. g. IBM SPSS, MS Excel, R, Python)
2. Reviewing data (e. g. working with surveys, questionnaires)
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3. Coding data
4. Data entry
In taking a qualitative approach, the aim is understanding. You may know only roughly in advance what you are looking for; the design emerges as the study unfolds, enabling a responsive approach to data collection and analysis, and, as researcher, you will often play a subjective role in data collection and analysis.
What does the data look like and how is it explored and analysed?
Data:
· Words, pictures, objects, sounds
· Activities, behaviour, attitudes
• In-depth interviews
• Direct observation
• Documentation
• Artefacts
• Time-consuming
• Less able to generalize Exploring the data:
· seek relationships between identified and emerging themes
· relate behaviour or ideas to biographical characteristics of respondents.
Steps in analysis method:
1. Familiarization with the data through repeated reading, listening, etc.
2. Transcription of interview, etc. material
3. Organization and indexing of data for easy retrieval and identification (e. g. by hand or computerized program such as NVivo, ATLAS. ti, Quirkos or Provalis)
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