A national census is an exercise that counts the population of a state, geographic region, or country. It is done to record information about the demographics of a population, which include sex, age, occupation, among others. The data acquired from the exercise can help in planning, research, and marketing purposes.
A national census is important because it helps the national government to have information on the total number of people living in its jurisdiction. The information is important because it helps the government efficiently administrate the country. It is a planning tool that helps the government effectively use its resources efficiently by putting in place adequate measures to plan for its population based on the knowledge provided by a national census.
In my view, the national census has a significant effect on life because it helps the country distribute resources and provide essential services in an effective manner. A fair distribution of resources enhances the living conditions of the population.
Biostatistics is a discipline that deals with the gathering, analysis, and interpretation of data that involves different attributes of a population. It applies a wide range of statistical methods to come up with conclusions that help understand the population under study. Similarly, the National census involves gathering, analyzing, and interpreting data acquired from a population concerning their size, age, sex, and gender, among other demographics. Therefore, there is a direct association between the national census and biostatistics.
The power of the studies could have been significantly reduced if they had a much smaller or limited number of participants instead of the number of participants that they had. Small sample size is not representative enough to support a valid research study. It is highly likely to increase the margin of error in the study and affect its accuracy.
On the other hand, if the researchers had too many participants in their studies which exceeded what they had, it would have significantly enhanced the accuracy of the studies. Studies involving too many participants are highly representative and have lower margins of errors. However, having too many participants puts a lot of strain on available resources in conducting studies. It is difficult to conduct studies involving too many participants because it presents logistical and financial constraints.
Both research articles have incorporated vital elements and power and sample size determination themes. The first article by Deb et al. (2022) used a sample size of 46 participant countries as a basis for its analysis. The sample size of 46 countries was sufficient to ensure that the margin of error was informative and small. The researchers determined the study’s sample size by being specific on the margin of error that was to be expected. The number of 46 countries was reasonable to provide a smaller margin of error with a confidence level of 95%. The key elements used in the study included using a larger sample size to reduce margins of error and increase the study’s accuracy. The second article by Kim et al. (2022) also used an appropriate sample size of 80 cohorts of radiography to reduce the margin of error in the study. The researchers ensured that the margin of error did not exceed a specific value by determining a sample size of 80 cohorts. It is an appropriate sample size that detected the differences between the control group and the experiment.
The margin of error affects the computation of a sample size in that an expectation of a higher margin of error leads to an increased number of participants while an expected lower margin can call for an optimal number of participants. The effect size represents a clinical significance outcome which is essential in determining the actual sample size to avoid a considerable margin of error. It is relevant in clinical practice and not statistically. However, it can be used to determine a study’s sample size. The standard deviation tests the variability of different hypotheses by computing test statistics to a relevant critical value. Confirming a hypothesis leads to selecting a sample size with the desired mean.
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References
Deb, P., Furceri1, D., Jimenez, D., Kothari, S., Ostry, J. and Tawk, N. (2022). The effects of COVID-19 vaccines on economic activity. Swiss Journal of Economics and Statistics, 158:3
Kim, C. Choi, J., Jiao, Z., Wang D., Wu, J., Yi, T., Halsey, K., Eweje , F., Tran, L., Liu, C., Wang, R., Sollee, J., Hsieh, C.,Chang, K., Yang, F., Singh, R., Qu, J., Huang, R., Feng, C., Feldman, M., et al.(2022). An automated COVID-19 triage pipeline using artificial intelligence based on chest radiographs and clinical data. NPJ digital Medicine.