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For the automated recognition of people based on intrinsic physical or behavioural traits, see Biometrics.

Biostatistics or biometry is the application of statistics to a wide range of topics in biology. It has particular applications to medicine and to agriculture.

Note on terminology: Although the terms "biostatistics" and "biometry" are sometimes used interchangeably, "biometry" is more often used of biological or agricultural applications and "biostatistics" of medical applications. In older sources "biometrics" is used as a synonym for "biometry", but this term has now been largely usurped by the information technology industry.

Contents 1 Biostatistics and the history of biological thought 2 Education and Training Programs 3 Applications of biostatistics 4 Related Fields 5 See also 6 External links 7 Journals 8 References

Biostatistical reasoning and modeling were of critical importance to the foundation theories of modern biology. In the early 1900s, after the rediscovery of Mendel's work, the conceptual gaps in understanding between genetics and evolutionary Darwinism led to vigorous debate between biometricians such as Walter Weldon and Karl Pearson and Mendelians such as Charles Davenport and William Bateson. By the 1930s statisticians and models built on statistical reasoning had helped to resolve these differences and to produce the Neo-Darwinian Modern evolutionary synthesis.

The leading figures in the establishment of this synthesis all relied on statistics and developed its use in biology.

• Sir Ronald A. Fisher developed several basic statistical methods in support of his work The Genetical Theory of Natural Selection
• Sewall G. Wright used statistics in the development of modern population genetics
• J. B. S Haldane's book, The Causes of Evolution, reestablished natural selection as the premier mechanism of evolution by explaining it in terms of the mathematical consequences of Mendelian genetics.

These individuals and the work of other biostatisticians, mathematical biologists, and statistically inclined geneticists helped bring together evolutionary biology and genetics into a consistent, coherent whole that could begin to be quantitatively modeled.

In parallel to this overall development, the pioneering work of D'Arcy Thompson in On Growth and Form also helped to add quantitative discipline to biological study.

Despite the fundamental importance and frequent necessity of statistical reasoning, there is nonetheless a tendency of biologists to distrust or deprecate results which are not qualitatively apparent. One anecdote describes Thomas Hunt Morgan banning the Frieden calculator from his department at Caltech, saying "Well, I am like a guy who is prospecting for gold along the banks of the Sacramento River in 1849. With a little intelligence, I can reach down and pick up big nuggets of gold. And as long as I can do that, I'm not going to let any people in my department waste scarce resources in placer mining."^[1] Educators are now adjusting their curricula to focus on more quantitative concepts and tools.^[2]

Almost all educational programmes in biostatistics are at postgraduate level. They are most often found in schools of public health, affiliated with schools of medicine, forestry, or agriculture or as a focus of application in departments of statistics. In the United States, several universities have dedicated biostatistics departments; many other top-tier universities integrate Biostatistics faculty into Statistics or other departments, such as Epidemiology (e.g. U of Oklahoma) . Thus departments carrying the name "biostatistics" may exist under quite different structures. For instance, relatively new biostatistics departments have been founded with a focus on bioinformatics and computational biology (e.g. U of Rochester(NY) and U of Louisville (KY) ) whereas older departments, typically affiliated with schools of public health, will have more traditional lines of research involving epidemiological studies and clinical trials as well as bioinformatics. In larger universities where both a Statistics and a Biostatistics department exist (e.g. U of Iowa, U of Minnesota, U of Washington) the degree of integration between the two departments may range from the bare minimum to very close collaboration. In general, the difference between a statistics program and a biostatistics one is twofold: (i) statistics departments will often host theoretical/methodological research which are less common in biostatistics programs and (ii) statistics departments have lines of research that may include biomedical applications but also other areas such as industry (quality control), business and economics and biological areas other than medicine.

• Public health, including epidemiology, health services research, nutrition, and environmental health,
• Design and analysis of clinical trials in medicine
• Genomics, population genetics, and statistical genetics in populations in order to link variation in genotype with a variation in phenotype. This has been used in agriculture to improve crops and farm animals. In biomedical research, this work can assist in finding candidates for gene alleles that can cause or influence predisposition to disease in human genetics
• Ecology
• Biological sequence analysis

Statistical methods are beginning to be integrated into medical informatics, public health informatics, and bioinformatics

Biostatistics draws quantitative methods from fields such as:

• statistics,
• operations research,
• computer science,
• economics, and, generally,
• mathematics

• Bioinformatics
• Mathematical biology
• Important publications in biostatistics

• Biometric System of Iris Recognition
• The International Biometric Society
• BIOREL resource for quantitative estimation of the gene network bias in relation to available database information
• The American Statistical Association
• The Royal Statistical Society
• The Collection of Biostatistics Research Archive
• The American Association of Schools of Public Health
• The Biostatistics Collaboration of Australia
• Guide to Biostatistics (MedPageToday.com)
• The Little Handbook of Statistical Practice

• Statistical Applications in Genetics and Molecular Biology
• Statistics in Medicine
• The International Journal of Biostatistics
• Journal of Biopharmaceutical Statistics
• Biostatistics
• Biometrics
• Biometrika
• Biometrical Journal