Outline two problems with using a random sample in sociological research.
AQA
A Level
2024
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Outline: Problems with Using a Random Sample in Sociological Research
This essay will explore two key problems associated with using random sampling in sociological research. Random sampling, while seemingly straightforward, can pose significant challenges when attempting to produce meaningful and reliable data. The two main problems addressed here are the difficulty in ensuring representativeness and the practical challenges associated with accessing and managing large sample sizes.
Problem 1: Representativeness
One significant problem with random sampling is the potential lack of representativeness. A simple random sample does not inherently guarantee a sample that accurately reflects the characteristics of the target population. This can lead to biased findings, as the sample may over-represent certain groups while under-representing others. For instance, a random sample of a university student body might accidentally over-represent students from specific faculties or year groups, thereby skewing the results of the study.
Problem 2: Practical Challenges
Beyond representativeness, random sampling presents practical challenges that can hinder its effectiveness. A major hurdle is the difficulty in obtaining a complete and accurate sampling frame. A sampling frame is a list of all individuals within the target population. Not all target populations have readily available sampling frames. For example, it would be extremely difficult to create a comprehensive sampling frame for all homeless individuals in a particular city. This lack of a reliable frame makes it impossible to select a truly random sample.
Furthermore, random sampling, especially for large populations, can be extremely expensive. The cost of accessing the necessary data, contacting participants, and conducting the research can be prohibitive, especially for researchers with limited budgets. This financial barrier can limit the scope and feasibility of using random sampling, particularly in resource-constrained research projects.
Finally, random sampling requires a large sample size to be truly meaningful and statistically reliable. Small random samples can be susceptible to significant sampling error, meaning the results might not accurately reflect the target population. However, obtaining a large sample can be time-consuming and resource-intensive, particularly for researchers studying sensitive or hard-to-access populations.
Conclusion
In conclusion, while random sampling offers a seemingly simple and objective method of data collection, it is not without its limitations. The challenge of ensuring representativeness and the numerous practical hurdles associated with its implementation necessitate careful consideration before employing this sampling technique. Researchers must weigh the potential benefits of random sampling against these drawbacks to determine its suitability for a specific research project.
Outline Two Problems With Using a Random Sample in Sociological Research.
Random sampling is a technique used by researchers when selecting participants for their study. A random sample is one where every member of the population has an equal chance of being selected. While random sampling is often seen as a desirable method, as it reduces bias, there are also some problems with using it. This essay will outline two problems with using a random sample in sociological research.
The first problem with using a random sample is that it is not always possible to achieve. In order to create a random sample, researchers need access to a sampling frame. A sampling frame is a complete list of everyone in the population the researcher is interested in studying. However, sampling frames do not always exist, particularly for hard to reach populations such as those experiencing homelessness. If the researcher does not have a sampling frame, or if it is incomplete, then the sample is not truly random. This can lead to a sample that is not representative of the population, which can bias the results of the study.
The second problem is that random samples can be very expensive and time-consuming to obtain. For example, if a researcher wanted to study a large population, such as all of the adults in the United Kingdom, it would be very costly to contact every single person on the electoral register and recruit them for the study. This is often not feasible for researchers who have limited time and resources. Researchers may not have the funding to cover the cost of postage, phone calls, or travel expenses to reach potential participants.
In conclusion, while random sampling is a valuable technique in sociological research, it is important to be aware of its limitations. The practical difficulties in obtaining a truly random sample mean that it is not always possible or desirable to use this method. Researchers must weigh the benefits of random sampling against the costs and choose the sampling method that is most appropriate for their research.
Free Mark Scheme Extracts
Disadvantages of Random Sampling
Not representative (1 mark); no guarantee that a simple random sample will generate a representative sample (+1 mark)
Difficulty of finding sampling frame (1 mark); sampling frames do not exist for all target populations (+1 mark)
Expensive (1 mark); for large samples it would be very expensive to access a list of the target population (+1 mark)
Need a large sample (1 mark); for random sampling to work there needs to be a large sample for it to be meaningful (+1 mark)
Need extra information about target population (1 mark); in order to stratify sample and make it more representative (+1 mark)