Difference in Population and Sample
Population describes the entire stakeholders of the United States healthcare system. These include the care providers, policy makers, healthcare leaders, and the rest of the citizens. A sample, on the other hand, describes one or more elements drawn from the population. These elements often contain certain similar characteristics to the population, and are used to obtain the study characteristics and patters of the population. In the context of this study, the sample could be individuals drawn from different states across the US. It is important to ensure that all the states are included in the study to obtain an accurate result. Also, it is worth noting that the study sample has to be comprised of all healthcare stakeholders.
It is impractical in standard settings to study a whole population with subjects such as the understanding of the US health care system. It is apparent considering the data collection methodologies that were selected to comprehend the notions of the public concerning the study subject. For the above reason, researchers utilize sampling methods; they surmise information concerning the population based on the outcomes of the population subset. By invalidating the need to investigate the entire population, it reduces both workload and time consumed. The overall outcome of the study is quality data attained from a large sample size with enough authority to identify correlation. Therefore, the population selected must represent the whole population.
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Sampling Techniques
The research would utilize probability sampling, whereby a framework for eligible participants is created. The qualified participants will then represent the entire population in the data collection processes that follow. The approach is preferred as it allows the data collected to be generalized easily; however, it will be at higher costs and more-time consumption. Though probability sampling offers a systematic approach to data collection, nonprobability sampling techniques solve the majority of probability sampling problems. Among them is time-consumed and cost as the methods do not rely on a framework the section process. The sample size is pre-determined; the drawbacks of the non-probability sampling method are the inability to generalize the data collected. Additionally, the approach is based on minimizing the time consumed, and it may result in inadequate data collection.
Probability sampling offers the best approach when executing the proposed data collection tactics. For the research elaborated in the dissertation, a simple random sampling method will be utilized. The approach utilizes the lottery method of representative selection from a pre-selected sample group that qualified the section process. The sampling methodology functions by relying on chance, the larger sampling group members are given opportunities to be selected again for the data collection. The approach under numerous applications has proven efficient in creating subset sample populations that offered the most significant representation of the larger population eliminating any form of bias that may occur. However, due to the scale of the project, the sampling population has to be larger, and the lottery method would have to rely on computers. It reduces the prospect of errors that are represented by either a plus or minus discrepancy. The sampling method's outcome is irrespective of the study subject, thereby offering numerous advantages when studying public health in the country. It should be noted that it was mentioned that the simple random sampling method has limited errors. However, the errors are also calculated and included in the process, thereby further reducing errors.
Nonetheless, the methodology is simple and straightforward, allowing for probability sampling to represent the entire population. However, it is limited by the fact that the research process may lack the adequate sample size. It is mostly experienced when searching for unique characteristics such as specific conditions and the population affected. Overall, it is acknowledged that simple random sampling does not offer a single listing that specifies the interests of the researchers. The result is more time consumed as well as increased expensed. However, the data collected and processed offers as a high representation of the population.
Accessing the Sample
The sample will be accessed using random and multistage sampling methods. In this case, the numbers will be randomly assigned to the population members, who will then be selected using a lottery system to represent the first cluster of the population. Given that this subset will be too large to be used as the study sample, a second step of random selection will be used. The two stages of random sampling will then give a manageable number of participants to be included in the study. The process has to be done separately for all the stakeholders involved, to minimize bias in accessing the sample of healthcare providers, policy makers, healthcare leaders, and care seekers.
