Quantitative research design is subject to many researcher choices including choice of specific study approaches, the tools of study, the analytical processes, and the populations targeted by the study. In each of these choices, the researcher is susceptible to bias. Bias results from the preference of one choice over another that arises due to subjective opinions. Bias can have negative results for a study. For instance, the results of quantitative research can be skewed in presentation, the research questions could be leading the respondents to specific answers, and findings could be wrong if the wrong participants are selected for research. In each of these outcomes, it is possible to reduce/ eliminate potential research bias in various ways. Panucci and Wilkins recommend reducing bias by clearly defining the risks and outcomes in research, standardizing data collection procedures, using objective data sources, selecting participants from common general populations, and using objective validation measures for research findings (622).
In the exercise carried out on determining what you know, it was possible to determine my extent of understanding/ lack of understanding various concepts of the course. Through the different questions, the ability to choose a right answer out of the multiple choices given was considered a reflection of good understanding of the concepts. On the other hand, wrong answers to questions indicated lack of understanding. Consequently, it is possible to deduce that while I have understood some of the concepts, I still have to explore more on particularly on the sample selection aspects. Through the activity, I have come to clearly know the areas in which I need to focus for a better understanding of the concepts. I know the areas of deficiency and I am capable of finding the right materials for reference.
Panucci, Christopher J. and Wilkins, Edwin G. Identifying and Avoiding Bias in Research. Plastic and Reconstructive Surgery, vol. 126, no. 2, 2010, pp. 619-625. www.ncbi.nlm.nih.gov/pmc/articles/PMC2917255/. Accessed on 7 June 2019.