The Sample Population and its Ethical Concerns

A sample is simply a subset of a bigger population. In this aspect, it is considered that the sample is representative of the entire population, allowing inferences to be drawn on behalf of the full population (Thompson, 2012). My sample population consists of people suffering from mental illnesses in the United States. This is primarily an adult population suffering from disorders such as depression, bipolar disorder, or schizophrenia. However, minors under the age of 18 may also suffer from mental illness, and this group may require parental approval.  It is no secret that there are millions of people suffering from mental illness in America. However, due to time and budget constraints, it is impossible to collect data from the entire population. In this case, sampling would be effective as it could save time and money. Usually, sampling is said to be unethical and erroneous if the sample size is not large enough to ensure that the sample has similar characteristics, traits, behaviors, qualities or figures as that of the entire population (Sapsford & Jupp, 2006). In my case, I will locate the sample population by conducting an online survey in order to gain valuable insights about the estimated population size (adults and children) suffering from mental illness. For instance, if it is estimated that approximately 100 million Americans (adults and children) suffer from mental illness each year, then this gives us a rough idea of the larger population size. We can then use sample size formula to determine the sample size.

The preferred sampling technique for this research is the stratified random sampling. This is due to the fact there are two groups (strata) of population to be studied. In this case, we have both children and adults suffering from mental illness. Each group needs to be fairly represented in the sample and therefore to ensure representativeness of the sample, we first divide the entire population into two groups (adults and children), and then pull out random samples from each group to be used in the research. To avoid sampling error, we need to ensure that the size of each sample is relative to the size of the whole group (Thompson, 2012). For instance, if there are 45 million adults suffering from mental illness, then the sample size needs to be a reasonable percentage of this entire population, say 1%. The main advantage of stratified sampling method is the fact that it eliminates bias that occurs as a result of randomly sampling different population groups together (Thompson, 2012).

References

Sapsford, R. & Jupp, V. (2006). Data collection and analysis (1st ed.). London: SAGE

Publications in association with the Open University.

Thompson, S. (2012). Sampling (1st ed.). Hoboken, N.J.: Wiley.