Your assignment is to create a research poster based on what you have learned in this course along with some of the material you have produced for writing assignments. Be sure to revise components acc

involves getting a representative sample from a population that has been separated into relatively

identical strata or subpopulations. To employ this sampling technique, I would first have to

divide the diverse population into relatively homogenous factions called strata. I would then

draw a random sample from each group and unite them to formulate a complete representative

sample. Stratified sampling has various advantages such as it provides precise and accurate

estimates for subgroups (Parsons, 2014). When dealing with a relatively homogeneous

subpopulation relative to the entire population, more accurate estimates of the subgroups can be

gotten through stratified sampling. In addition, stratified sampling ensures efficiency in

surveying by simplifying data collection and reducing survey costs (Parsons, 2014). Moreover,

explicitly incorporating the strata into the sampling methodology ensures that all groups of

interest are represented in the study. Stratified sampling also has certain disadvantages such as it

requires the researcher to come up with a scheme for the strata to include all members of the

population. Furthermore, stratified sampling might be ineffective if the researchers lack enough

information to assign subjects to the correct strata (Parsons, 2014).

The second probability technique is cluster sampling which requires populations to be

placed into separate groups. A random sample of the groups is then selected to represent a

specific population. Cluster sampling has various advantages such as, it reduces the number

required to generate accurate data thereby allowing for research to be conducted with a reduced

economy. Moreover, when clusters are appropriately put together, they provide a more accurate

estimation process thereby reducing variability. Cluster sampling is a more feasible approach

since it eliminates the need to manage large data inputs (O’Malley et al., 2020). On the other

hand, cluster sampling has certain disadvantages such as it makes it easier for the researcher to 3 come up with biased data. Moreover, the skills of the researcher have a great impact on the

information collected through cluster sampling. As such, if the data collection skills of the

researcher are subpar, the information collected may be irrelevant. Cluster sampling also needs

equality in size for the process to come up with accurate solutions (O’Malley et al., 2020). 4 References O’Malley, A. J., & Park, S. (2020). A novel cluster sampling design that couples multiple

surveys to support multiple inferential objectives. Health Services and Outcomes Research

Methodology, 20(2), 85-110.

Parsons, V. L. (2014). Stratified sampling. Wiley StatsRef: Statistics Reference Online, 1-11.