Secondary research is simple and can get done in just four steps, as explained in this article. It involves looking at data that was collected by somebody else, and you can get the data through past researchers, government archives, or online platforms. You get to reanalyze, interpret, and review the collected data in this case.
When you utilize a secondary data set on its own, the purpose is typically to have a re-assessment of data while posing a different research question. When one decides to use a pair of data sets to do research, it gets typically meant to find out the relationship between the variables available in them or to have a comparison on the outcomes from the past research. On the other hand, when you decide to combine both primary and secondary data sets, they want to obtain pieces of information that are already existing but one that informs the primary research.
Secondary data can use both qualitative and quantitative types. In quantitative data type, the researcher aims at informing the current research with past retrieved data. He/she is also aiming at re-assessing the set of data from the past. Qualitative type gets used when the researcher wants to bolster the current research with the retrieved data.
For most undergraduate students, the supervisors give them the research questions, but the same does not apply to other levels. You will need to be specific about the area of your research. You then need to read through past papers to find a gap to fill with your research. Afterward, you will specify the research question.
You will do this when you come to the discovery of past data that can get well applied in your work to help you nail the question in a detailed form. You will review your literature and identify other researches or centers that have handled the topic you have before. You will need to get permission from the authors to utilize the data set that you will have collected.
To do this right, you will need to know the aim of your study, as the original author’s purpose could be way different from yours. Note the differences in the purposes of research in the data sets.
In this step, get familiar with past research. Outline all the variables you will need in your research. When done, identify and label the missing data. Create new variables and compute them if necessary. Lastly, analyze the data.