The PICOT question guiding the project is, “in patients who are seen in the emergency department, how does being short-staffed compared to being fully-staffed influence patient satisfaction during their emergency room (ER) visit?” This paper demonstrates how statistical theory can be employed to support the proposed solution to this research question.
Theory and Justification for Selection
The statistical theory can be described as “the rigorous study of the procedure of extracting information from data using formalism and machinery of mathematics” (Abramovich & Ritou, 2013, p. 6). Available literature demonstrates that the statistical theory not only avails a framework for a whole range of techniques in both study design and data analysis that could be used to solve problems, but also covers approaches to statistical-decision problems and statistical inference by identifying a phenomenon or sample of interest and striving to understand how the various variables under study influence the phenomenon or sample (Epps, 2013). The justification for selecting the theory, therefore, is embedded in its capacity to use statistics to identify how various factors related to staffing ratios influence patient satisfaction during the emergency room visit.
How Theory Works to Support Proposed Solution
The statistical theory provides a multiplicity of ways that could be used to compare statistical procedures (e.g., descriptive statistics and inferential statistics), not mentioning that it has the capacity to find the best possible procedure within a given context or to provide appropriate guidance on the statistical procedures a researcher may choose from the available alternatives (Abramovich & Ritou, 2013). In this particular case, the researcher is interested in finding a solution on how various staffing ratios (short-staffed and fully-staffed) influence patient satisfaction during ER visit. Consequently, the theory works to support the proposed solution by assisting the researcher to not only develop a statistical framework through which he can think of data as outcomes of probability experiments, but also to learn something about the population based on the sample through the use of descriptive or inferential statistical analysis (Epps, 2013).
Incorporating the Theory into the Project
The statistical theory, which has been developed to necessitate the extraction of information from raw data using formalism and machinery of mathematics, allows the researcher to study how various staffing ratios (short-staffed and fully-staffed) influence patient satisfaction during ER visit. The theory has the potential to enrich such a research project through enhanced validity and greater attention to both heterogeneities of effects and causal processes producing different types of patient satisfaction levels depending on staffing ratios, not mentioning that it may serve to test and develop new theories. However, the statistical theory needs to be incorporated into the project through the employment of a quantitative research design and a positivist paradigm, implying that field data will be collected and converted into numerical format in order for statistical calculations to be made and conclusions drawn (Epps, 2013).
Overall, this paper has demonstrated how the statistical theory can be applied to support the proposed solution to the research project.
References
Abramovich, F., & Ritou, Y. (2013). Statistical theory: A concise introduction. Boca Raton, FL: CRC Press
Epps, T.W. (2013). Probability and statistical theory for applied researchers. London: World Scientific Publishing Co.