Practice Reflection on Biostatistics in Public Health Policy, Planning, and Management

Running head: PRACTICE REFLECTION 1
Practice Reflection
Name:
Institutional Affiliation

PRACTICE REFLECTION 2
Practice Reflection
Biostatistics is the application of statistics to biological experiments (Idrayan, 2012). The
course entails designing of biological experiments, data collection, summarization, and analysis
as well as interpretation and inference of results obtained from biological experiments.
Biostatistics is applied in public health such as epidemiology, nutrition, environmental health,
healthcare policy, and health service research (Overholser, 2017). The course has provided in
depth knowledge in different aspects of biological experiments that are fundamental to practice
in public health and healthcare policy and management. Basically, the course has impacted me
on the causes of diseases including environmental, genetic, and lifestyle among populations. The
aim of this reflection is to explore the concepts learnt in the biostatistics course and how those
concepts have shaped my future practice in the field of public health policy, planning, and
management.
To begin with the concept of correlation and regression has enabled me to establish the
existence of an association between two continuous variables and assess the mathematical
relationship between two variables. As articulated by Sullivan (2013), correlation coefficient
gives the strength and direction of association. In particular, the understanding of concepts of
correlation and regression analysis places me in a better position to accurately establish the
relationship between risk factor and outcome of diseases in public health. In addition, the
concept of risks has equipped me to establish the causal relationship between exposure and
outcome as well as the strength of association. Specifically, relative risk and attributive risks
provide an accurate means of determine the strength of relationship between the exposure and
outcome of a disease (Kirkwood & Sterne, 2013). In addition, the concept of causation, bias,
confounding, and adjustment is critical in establishing cause and effect relationship. Elimination

PRACTICE REFLECTION 3
of bias and adjustment of factors that both influence the outcome are fundamental requirements
for accurate determination of cause-effect relationships as expounded by Stoddard (2014).
Analysis of variance is another crucial concept learnt in biostatistics. In this chapter, the
importance of determining whether means are statistically different was covered. The chapter
was important in assessing the accuracy of data collected through computation of means.
Further, the determination of outliers among the data collected was examined in non-parametric
tests. Outliers are data which are significantly different from other data in a set. Exclusion of
outliers is a fundamental requirement in ensuring that the results obtained from an experiment
are accurate. In relation to health policy, planning, and management, analysis of variance is vital
in ensuring that policies developed towards addressing healthcare issues are derived from
accurately determined results of biological experiments.
Meta analysis was the final chapter in biostatistics that shaped my practice in relation to
health planning, and management. In particular, this chapter shaped my appreciation of research
translation and understanding of types of research translation. As expounded by National Health
and Medical Research Council (2014), development of knowledge through research is critical to
improvement of health service delivery and intervention. Improvement of service delivery in the
health care sector is influenced by effecting healthcare planning and management. As a result, in-
depth understanding of Meta analysis is a basic requirement for effective health palling and
management. In addition, the concept of systematic reviews concisely covered in this chapter is
an important aspect of research. Systematic review is provides a means of distilling and sorting
of research work in order to assess the quality of the study, degree of bias, and reporting bias.
Health planning and management rely on results of biological experiments conducted by
different researchers. Before search experiments are used in policy development, it is important