Blog Post#7: Analyzing Primary Research Data
Hi everyone! I just got off reading through 25 pages of 'How To Analyse Data in a Primary Research Study' today and I could not wait to share my first thoughts about it! The authors Melody Denny and Lindsay Clark in their article mention the difference between primary and secondary research. Secondary research makes use of sources mostly found in the library or online (books, journal articles, magazines, etc). However, primary research is any type of research we collect ourself, that includes interviews, observations, and surveys. Primary research is of two main types: quantitative and qualitative research. Quantitative research deals with numerical data. Qualitative research deals with answering the whys and hows of human behavior, opinion, and experience.
The authors further highlight that primary research provides opportunities to collect information based on your specific research questions and generate new knowledge from those questions to share with others. It follows 5 steps including developing a research question, deciding on a research method, collecting data, analysing data, and reporting findings.
There are two types of questions to consider in order for the researchers to answer their research questions: closed-ended and open-ended. Closed ended questions make data analysis a bit easier since the way respondents could answer those questions is limited to specific answers. The data can be analyzed by each question or by looking at the responses individually or as a whole. But, how we ask the question determines the type of data we collect. Open ended questions, which can provide fruitful responses, can also mean unexpected responses or responses that don’t help to answer the overall research question, which can sometimes make data analysis challenging. The authors mention using the open coding technique, i.e., analyzing the data without any predetermined categories or themes; researchers are just seeing what emerges or seems significant. They highlight that there are four specific steps when coding qualitative data including how we ethically coded the data, interpreted what the coding process revealed, and worked together to identify and explain categories we saw in the data.
In fact, I came across something similar while reading about a chapter on 'Analysing Data in Qualitative Research' from the book 'Nursing and Midwifery Research: Methods and Appraisal for Evidence Based Practice' by Zevia Schneider et al. In the chapter, one of the important things the authors discuss is the three major styles for analysis of qualitative data including coding and categorising, constant comparison, and thematic analysis. They also highlight a more recent significant approach to qualitative research, i.e., meta synthesis. Here is the link to this book:
There is also an interesting video on this topic that explains the fundamentals of analysing data, one of the qualitative research methods: