Data collection and analysis
For the purposes of compliance with ethics and data storage policies, 'data' means 'original information which is collected, stored, accessed, used or disposed of during the course of the research, and the final report of the research findings'.
Your research methods may include the collection of information (data) which can be interpreted or analysed to frame answers to your research questions or increase knowledge of your research topic. You can collect this information in a variety of ways (interviews, surveys, experiments, observations, critical appraisal of texts, literature or works of art or other artefacts). Different collection methods will require different types of management.
Numerical or quantitative information is obtained from research methods such as surveys of populations or from repeated experimental procedures. When recording the data it is important to include detailed information (eg dates and place of collection, methods of measurement, units of measurement) to minimise confusion. Numerical data are usually recorded on printed datasheets, then stored in spreadsheet format.
In some cases, data may initially be recorded by handheld computers or specialised data recorders which can later be downloaded to more secure devices. Data recorders can often be set up to record data remotely, without the requirement that researchers be present. Such techniques are frequently used in meteorological research or in situations where it would be too hazardous for a researcher to be present (eg industrial chemistry applications, space research).
Software and training
Specialist statistics software such as SPSS (Statistics Package for Social Scientists) are available on campus computer pools by UniSA site license. If you are an external or offshore student, contact your supervisor to make other arrangements for data analysis.
A short course on statistics may help you analyse your data. Your supervisor should be able to direct you to an appropriate course or consultative service.
Qualitative (non-numerical) information may be recorded during interviews with human participants, often on video or audiotape, possibly with supporting notes, and may be transcribed into written form later. Other qualitative information describing and interpreting texts or artefacts may also be recorded in written form and stored on index cards or as Word files. This material may be coded for themes using software programs (eg Nvivo) that search for keywords or strings, or it may be done manually. The transcripts may also be treated as texts for analysis.
Visual information may be recorded as photographic plates, slides, computerised files or hand-drawn diagrams.
Software and training
The University has purchased QSR NVivo software licences for research degree students in the Divisions of Business; Education, Arts and Social Sciences; and Health Sciences.
NVivo software helps you access, manage, shape and analyse detailed textual and/or multimedia data by removing manual tasks like classifying, sorting and arranging information. NVivo can:
- examine virtually any qualitative or textual information, from in-depth interview and focus group transcripts to documents, field or case notes
- be used for a wide range of research methods, including network and organisational analysis, action or evidence-based research, discourse analysis, grounded theory, conversation analysis, ethnography, literature reviews, phenomenology and mixed methods research.
If you a student from a division which has this software and you wish to use it to analyse your data, you can apply to have it installed on your pc free of charge. Go to the UniSA Software Licensing website, read the instructions, follow the link to QSR/NVivo, and download the Software Licence Application.
Your division may offer training opportunities in NVivo.
The data or information you initially collect is often in a bulky format (spreadsheets of numerical data, transcripts of interviews, or descriptions of artefacts) which need to be summarised, interpreted and analysed before you can draw conclusions.
It is often best to summarise information to identify patterns. Summarising helps you to compare information in a standardised format so that you (or your reader) does not have to sort through a lot of information to make comparisons. For example:
- When interpreting interview data you can prepare tables listing frequently-raised issues of interviewees under categories such as age or gender.
- Numerical data can usually be summarised mathematically, as means (averages), medians, modes or frequencies.
Once information is summarised, you will find it easier to identify patterns and interpret meanings. Sometimes this can be a simple descriptive process if patterns or meaning are obvious.
When writing conference papers, posters, publications or your thesis, you will need to present your information clearly. Using figures (diagrams, photographs, maps, graphs) or tables (lists of written or numerical information) will enable you to demonstrate your arguments clearly.
Figures and tables must:
- be numbered consecutively
- be correctly referred to (by number) and relevant to the text
- be presented in a consistent style
- have a descriptive caption so that they can be understood without text if necessary (captions usually go above a table, and below a figure)
Graphs must have axes labelled and all units of measurement clearly shown.
Information such as raw data tables, photographs of specimens, or artefacts may be more appropriately inserted as appendices.