Data Quality Issues in a Sampling Survey

Abstract:

Getting data that can be said to be simple, meaningful, accurate, reliable and timely (SMART) is the uphill task of a good population based researcher. How to get a smart, complete and unbiased data is a harder task to accomplish. The good news however, is that it is doable if the right techniques are applied. The right approach is to strictly adhere to the dos and don’ts rule governing the planning and fieldwork processes of data collection. In order to ensure that data has integrity, the monitoring, evaluation and research officer must begin the process from the data collection planning stage. In a survey research and indeed any scientific study, there are seven stages that the research process must pass through; from the detection of problem to application of solution. This is called the stages of research.  They include the identification of problem, the planning, the selection of goal, the selection of methodology, collect data with trained interviewers, analyze data and act on data.

Each of the seven steps discussed so far has some data quality implications involved, if you must get your goal right. Neglecting all or some key ones, may ruin the efficacy of what would have been some good findings. Either in the field of purely physical sciences or social sciences, once the methodology presented in a study is faulty, the entire findings cannot be valid and the recommendations are null and void.

Researchers have ethical obligations to take into account when conducting study involving the human elements. These include Non-violation of personal rights, security of the participants, confidentiality of information and getting informed consent from a respondent among others. Beyond ethical consideration, for a researcher to get unbiased responses from the respondents, the data collectors must observe some basic socio-cultural codes, which you can describe as norms of data collection. They include proper protocol review, equal access to information by the participants, courtesy visit to significant persons, advocacy visit to deserving authority, observe local greeting ethics and dressing code, questioning well, listening well and recording well. Not listening attentively is a weakness. It is a sign of impatience. Remember the saying “a patient dog eats the fattest bone”. Inpatient persons often lose out in a contest. Inpatient interviewers may even turn off people who have valuable information to provide; and one turn-off may discourage the respondent from continuing the responses with even more valuable information.

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APA

Nwizugbe, E. & PhD, N (2018). Data Quality Issues in a Sampling Survey. Afribary. Retrieved from https://track.afribary.com/works/data-quality-issues

MLA 8th

Nwizugbe, Ezenwa, and Nwizugbe PhD "Data Quality Issues in a Sampling Survey" Afribary. Afribary, 25 Apr. 2018, https://track.afribary.com/works/data-quality-issues. Accessed 25 Dec. 2024.

MLA7

Nwizugbe, Ezenwa, and Nwizugbe PhD . "Data Quality Issues in a Sampling Survey". Afribary, Afribary, 25 Apr. 2018. Web. 25 Dec. 2024. < https://track.afribary.com/works/data-quality-issues >.

Chicago

Nwizugbe, Ezenwa and PhD, Nwizugbe . "Data Quality Issues in a Sampling Survey" Afribary (2018). Accessed December 25, 2024. https://track.afribary.com/works/data-quality-issues