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Introduction
Efficient decision-making is crucial to any organization, particularly those dealing with humans such as healthcare organizations. Without loss of generality, other institutions that do not provide non-human services are also dependent on effective decision-making. Statistical analysis forms the basis through which many organizations make their decisions. Among all types of statistics, descriptive statistics is important in visualization of data such that the information can be easily comprehended by even non-statisticians.
Importance of Statistics in a Healthcare Organization
Descriptive statistics are useful that is why they are employed in different organizations. In my current professional industry, the healthcare field, I would employ the graphical and pictorial methods to provide a visual representation of data. Specifically, I would use histograms to indicate the frequencies with which each value of a variable such as prevalence of certain disease, death rate among adults, occurs (Kaur et al., 2018). In addition, I would use the scatterplot to display a relationship between two variables such as age, and the occurrence of a particular ailment (Kaur et al., 2018). However, graphical and pictorial methods are not limited to scatterplots and histograms alone.
I might use the clinical trials to make decisions that pertain to the healthcare institution in which I work. Since I deal with public health, this type of research is important because it enables me to understand new and existing medicine, surgeries, medical instruments among the healthy individuals and people with certain medical conditions. As such, I am able to assess the effectiveness of a new drug, diet, medical equipment on the general public.
The use of statistics in a healthcare organization would presume many forms in a myriad of contexts. I would use statistics to determine whether there has been an increase in risk factors for a sickness disease and advise the healthcare organization to allocate additional funds for interventions towards the disease prevention (Kaur et al., 2018). Indeed, allotment of the public or private funds determines how future research endeavors should be focused.
Overall, this is a good course because of some of the assignments or learning outcomes are beneficial. For example, the assignment on statistical analysis report is important because it has equipped me with the skill of being able to generate statistical reports and business reports for both my current and future organizations. In addition, the hypothesis testing is a learning area that has helped me to develop an analytic mindset that is important in determining the type of relationships between variables in my research areas (Kaur et al., 2018). Accordingly, I believe that the aforementioned learning areas will help me sharpen my research skills.
Having benefited from the learning experience in this course, I would not recommend many changes to the course. Nevertheless, I would propose that the assignment on data analytics should be given on each day from the onset to the end of the course. This is important because it will enable the students to have a permanent understanding of data analysis. Again, the daily practice would enable students to appreciate the essence of data in driving organizational goals in the current dispensation of technology.
Conclusion
In summary, descriptive statistics gives a pictorial or graphical representation of data for easy understanding. Variables such as age, mortality rate, morbidity, can be summarized under descriptive statistics and the relationship between them determined. In the context of healthcare organizations, the data can be used to establish treatment interventions that applicable to a certain disease. Funds allocation for various diseases is also done in line with the statistical analysis reports recommendations. Undoubtedly, statistics is an important resource in organizational decision-making and management.
Reference
Kaur, P., Stoltzfus, J., & Yellapu, V. (2018). Descriptive statistics. International Journal of Academic Medicine, 4(1), 60-63. Web.
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