Week 2 discussion - Assignment Example

Week 2 Discussion Discuss the advantages and disadvantages of at least 2 different sampling methods Random sampling technique is most suitable when all the study subjects participate (Simmons, Nelson, & Simonsohn, 2011). It highly represents the population and can be useful in studies of limited resources. However, random sampling is a population bias since it does not represent all subjects. Random sampling is also uneconomical and disruptive as it isolates some members from the population. The data sample can also change implying that it is not possible to achieve reliability.

Stratified random sampling collects data from distinct groups ensures the representation of all subjects in the population (Simmons, Nelson, & Simonsohn, 2011). The technique involves arranging data into strata that results in even and proportional distribution of the sample. However, the technique is more complex and requires more resources. It is also difficult to define strata groups.Describe how researchers go about selecting a sampling strategy Researchers make sure that the sampling strategy aligns with the goals and objectives of the study.

Therefore, it is necessary to list research goals then the research proceeds to identify the sampling methods that fulfill the research mission(Simmons, Nelson, & Simonsohn, 2011). In this case, researchers choose the best method that achieve the goals of the research and aligns toWhat role does the research question play in choosing the sample? The research question gives direction to study by giving a hint of variables to measure (Simmons, Nelson, & Simonsohn, 2011). In this case, it influences the sampling technique since the researcher evaluates effectiveness of his or her methods based on the proposed variables.

On the other hand, the research question highlights the approach to use in the study thus gives the direction on the sample size to use. What does it mean to have a representative sample and why is this vital to the outcome of the study? A representative sample is a part of the statistical population that reflects all members of the population (Simmons, Nelson, & Simonsohn, 2011). A representative sample reduces the chances of research biases. A piece of research with good representative sample has least biases and represents all the subjects within the population.

It is important as it affects the accuracy and reliability of the study outcomes. ReferenceSimmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). False-positive psychology undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological science, 22(11), 1359-1366.