Abstract:

Biostatistics is the application of statistical techniques to biological data obtained prospectively and/or retrospectively. Statistics plays critical analytical role in biomedical research. It is the bases for building clear inference from the data collected in a biomedical evaluation and without which it would be impossible to declare an outcome from any clinical trial. This critical role of biostatistics in biomedical research was noted by Cadarso-Suárez, and González-Manteiga, (2007), who stated that “the discipline of biostatistics is nowadays a fundamental scientific component of biomedical, public health and health services research” and pointed out traditional and emerging areas of application as “clinical trials research, observational studies, physiology, imaging, and genomics”.

At the same time, misuse of biostatistics has resulted in several misleading outcomes and several workers have progressively noted the many statistical errors and shortcomings found in a large number of biomedical publications (Porter, 1999; Cooper, et al., 2002; García-Berthou and Alcaraz 2004; Strasak, et al., 2007; Ercan, et al., 2007; Thiese, et al., 2015). Ercan, et al., (2007) specifically notes that this observations cuts across “every stage of a medical research related to data analysis; design of the experiment, data collection and pre-processing, analysis method and implementation, and interpretation”. Similarly, Thiese, et al., (2015), points to data abuses such as “incorrect application of statistical tests, lack of transparency and disclosure about decisions that are made, incomplete or incorrect multivariate model building, or exclusion of outliers”.

The role of statistics in medical research starts at the planning stage of a clinical trial or laboratory experiment to establish the design and size of an experiment that will ensure a good prospect of detecting effects of clinical or scientific interest. Statistics is again used during the analysis of data (sample data) to make inferences valid in a wider population. Specifically, statistics has two roles in laboratory experiments and clinical trials.

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