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Medical statistics (also health statistics) deals with applications of statisticstomedicine and the health sciences, including epidemiology, public health, forensic medicine, and clinical research.[1] Medical statistics has been a recognized branch of statistics in the United Kingdom for more than 40 years, but the term has not come into general use in North America, where the wider term 'biostatistics' is more commonly used.[2] However, "biostatistics" more commonly connotes all applications of statistics to biology.[2] Medical statistics is a subdiscipline of statistics.
It is the science of summarizing, collecting, presenting and interpreting data in medical practice, and using them to estimate the magnitude of associations and test hypotheses. It has a central role in medical investigations. It not only provides a way of organizing information on a wider and more formal basis than relying on the exchange of anecdotes and personal experience, but also takes into account the intrinsic variation inherent in most biological processes.[3]
In medical hypothesis testing, the medical research is often evaluated by means of the confidence interval, the P value, or both.[4]
Frequently reported in medical research studies is the confidence interval (CI), which indicates the consistency and variability of the medical results of repeated medical trials. In other words, the confidence interval shows the range of values where the expected true estimate would exist within this specific range, if the study was performed many times.[1]
Most biomedical research is not able to use a total population for a study. Instead, samples of the total population are what are often used for a study. From the sample, inferences can be made of the total population by means of a sample statistic and the estimation of error, presented as a range of values.[1][4]
Frequently used in medical studies is the statistical significance of P < 0.05.[4]
The P value is the probability of no effect or no difference (null hypothesis) of obtaining a result essentially equal to what was actually observed. The P stands for probability and measures how likely it is that any observed difference between groups is due to chance. The P value function between 0 and 1. The closer to 0, the less likely the results are due to chance. The closer to 1, the higher the probability that the results are actually due to chance.[4]
Pharmaceutical statistics is the application of statistics to matters concerning the pharmaceutical industry. This can be from issues of design of experiments, to analysis of drug trials, to issues of commercialization of a medicine.[1]
There are many professional bodies concerned with this field including:
Clinical biostatistics is concerned with research into the principles and methodology used in the design and analysis of clinical research and to apply statistical theorytoclinical medicine.[1][5]
Clinical biostatistics is taught in postgraduate biostatistical and applied statistical degrees, for example as part of the BCA Master of Biostatistics program in Australia.
