Random Sampling

Random Sampling

When studying a given population, it is always difficult to conduct an analysis and learn the characteristics of every individual of the group. A challenge that may arise during research on a population is bias where the researcher has a specific taste of the individuals from which he collects the information.

Therefore, a method had to be created that can help give a clear understanding of a population by studying a small part of it and using the findings to generalize the whole group.

Random sampling is a selection method whereby a subset of a community is selected to represent the entire group with each member having an equal opportunity of being chosen. The technique is instrumental in samples collection which helps reduce a biased representation of the whole group and gives more accurate information.

Challenges faced in the accuracy of data collection when using random sampling include:

Lack of guarantee that the results obtained from the selected few are universal. It may be a coincidence, and the selected sample or most of it has the same ideology.

It leads to a conclusion of an idea that is not supported by the whole population because the majority of the entire group may not be represented in the sample.

It is a challenge which can be taken care of by selecting several subsets and conducting the data collection process severally. Information collected after all these processes is then compared to come up with useful data.

Biases from the data collector by choosing which information to keep on record is a significant challenge faced when using random sampling. Data collectors can control the research direction through manipulation of the collection process. The problem can only be solved by collecting information from the selected sample more than twice using different data collectors and then making a comparison.

A population diverse in its characteristics is also a problem that affects data collection when using random sampling method. In such a population individuals have different features even though they live and share the same environment. It is challenging to generalize a character in such a population since everyone has his unique way of living. A large sample for the study has to be formed to manage accurate data collection in such a community. More people have to be interviewed, and a comparison made among the collected data to determine the similarities.

Random Sampling