Discussion: Measures of Central Tendency

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Sampling Methods

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Stratified Random Sampling

I would use stratified random sampling, a probabilistic sampling method, to research high rates of substance abuse. Stratified sampling is a technique of sampling that entails population division into smaller sub-groups called strata (Zhao et al., 2019). The strata formation is relative to members’ shared characteristics or attributes such as educational attainment or income. After dividing the population into groups, the researcher randomly chose the sample proportionally. The strata should be distinct, and the data must not overlap. The method allows researchers to attain a sample population that appropriately represents the whole study population.

Strengths and Weaknesses

One advantage of the research method is that if the rehabilitation centers require improvements, research information could be a step in the appropriate direction to address any underlying problems. Another advantage is that it ensures every subgroup in the population gets proper representation in the sample. In this case, the technique offers better population coverage as the researchers have a mandate over the subgroups to facilitate the representation of all substance abusers and community members in the sampling. On the other hand, one of the technique’s disadvantages is that the researcher must meet several conditions for its proper use. For instance, a researcher should identify study population members and classify every one of them into only a single subpopulation. Another disadvantage is the participants’ refusal to offer accurate information during the research. For instance, failing to gather information face to face taints results.

Use

Stratified random sampling would help in obtaining information concerning drug abuse in the United States. My data collection form would be using surveys to gather information from community members and substance abusers in rehabilitation centers. In this case, I would use the research method for finding the general effectiveness, explanation, or applicability of the existing drug policies or programs.

Reference

Zhao, X., Liang, J., & Dang, C. (2019). A stratified sampling based clustering algorithm for large-scale data. Knowledge-Based Systems, 163, 416-428.