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Information about Biostatistics

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.

Biostatistics and the history of biological thought

Biostatistical reasoning and modeling were critical information of 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. 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]

Education and Training Programs

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.

Many universities that deal with ecological research have a biostatistics course that introduces concepts such as hypothesis testing for univariate and sometimes multivariate data sets with one, two, or more samples. Often this is combined or followed with some kind of experimental design course.

Applications of biostatistics

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

Related Fields

Biostatistics draws quantitative methods from fields such as:

See also

External links

Journals

References

Biometrics (ancient Greek: bios ="life", metron ="measure") is the study of methods for uniquely recognizing humans based upon one or more intrinsic physical or behavioral traits.
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Statistics is a mathematical science pertaining to the collection, analysis, interpretation or explanation, and presentation of data. It is applicable to a wide variety of academic disciplines, from the physical and social sciences to the humanities.
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Biology (from Greek: βίος, bio, "life"; and λόγος, logos, "knowledge"), also referred to as the biological sciences, is the scientific study of life.
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Medicine is the science and "" of maintaining and/or restoring human health through the study, diagnosis, and treatment of patients. The term is derived from the Latin ars medicina meaning the art of healing.
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Agriculture (from Agri Latin for ager ("a field"), and culture, from the Latin cultura "cultivation" in the strict sense of "tillage of the soil". A literal reading of the English word yields "tillage of the soil of a field".
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For the taxonomical term, see .


Synonyms (in ancient Greek, συν ("syn") = plus and όνομα ("onoma") = name
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Information technology (IT), as defined by the Information Technology Association of America (ITAA), is "the study, design, development, implementation, support or management of computer-based information systems, particularly software applications and computer hardware.
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Centuries: 18th century - 19th century - 20th century

1870s 1880s 1890s - 1900s - 1910s 1920s 1930s
1900 1901 1902 1903 1904
1905 1906 1907 1908 1909

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Events and trends

Technology


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Genetics is the science of heredity and variation in living organisms.[1][2] Knowledge of the inheritance of characteristics has been implicitly used since prehistoric times for improving crop plants and animals through selective breeding.
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Darwinism is a term for the underlying theory in those ideas of Charles Darwin concerning evolution and natural selection. Discussions of Darwinism usually focus on evolution by natural selection
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Walter Frank Raphael Weldon (15 March 1860 — 13 April 1906) was an English evolutionary zoologist and biometrician.

Biography

Weldon was the second child of the journalist and industrial chemist, Walter Weldon, and his wife Anne Cotton.
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Karl Pearson

Karl Pearson
Born March 27 1857(1857--)
London, England
Died March 27 1936 (aged 79)
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Charles Benedict Davenport (June 1, 1866–February 18, 1944) was a prominent American biologist and eugenicist.

Biography

Davenport was born in Stamford, Connecticut. He went to Harvard, getting a PhD in biology in 1892. He married in 1894.
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William Bateson (August 8, 1861 – February 8, 1926) was a British geneticist. He was the first person to use the term genetics to describe the study of heredity and biological inheritance, and the chief populariser of the ideas of Gregor Mendel following their rediscovery in
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Centuries: 19th century - 20th century - 21st century

1900s 1910s 1920s - 1930s - 1940s 1950s 1960s
1930 1931 1932 1933 1934
1935 1936 1937 1938 1939

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- The 1930s
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The modern evolutionary synthesis refers to a set of ideas from several biological specialities that were brought together to form a unified theory of evolution accepted by the great majority of working biologists.
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Ronald Fisher

Sir Ronald Aylmer Fisher
Born 17 January 1890(1890--)
East Finchley, London , England
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The Genetical Theory of Natural Selection is a book by R.A. Fisher. It was first published in 1930 by Clarendon. It is one of the most important books of the modern evolutionary synthesis and is obligatorily cited in biology books. The great biologist W. D.
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Sewall Green Wright ForMemRS (December 21, 1889 – March 3, 1988) was an American geneticist known for his influential work on evolutionary theory and also for his work on path analysis. With R. A. Fisher and J.B.S. Haldane, he was a founder of theoretical population genetics.
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Population genetics is the study of the allele frequency distribution and change under the influence of the four evolutionary forces: natural selection, genetic drift, mutation and gene flow. It also takes account of population subdivision and population structure in space.
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J. B. S. Haldane

J. B. S. Haldane
Born November 5 1892(1892--)
Oxford, England
Died November 1 1964 (aged 72)
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Evolutionary biology is a sub-field of biology concerned with the origin and descent of species, as well as their change, multiplication, and diversity over time.
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Genetics is the science of heredity and variation in living organisms.[1][2] Knowledge of the inheritance of characteristics has been implicitly used since prehistoric times for improving crop plants and animals through selective breeding.
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D'Arcy Wentworth Thompson (May 2, 1860–June 21, 1948) was a biologist, mathematician, classics scholar and the author of the 1917 book, On Growth and Form, an influential work of striking originality.
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Thomas Hunt Morgan (September 25, 1866 – December 4, 1945) was an American geneticist and embryologist. Morgan received his PhD from Johns Hopkins University in 1891 and researched embryology during his tenure at Bryn Mawr.
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California Institute of Technology (commonly referred to as Caltech)[1] is a private, coeducational research university located in Pasadena, California, in the United States. Caltech maintains a strong emphasis on the natural sciences and engineering.
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Postgraduate education (often known in North America as graduate education, and sometimes described as quaternary education) involves studying for degrees or other qualifications for which a first or Bachelor's degree is required, and is normally considered to be part
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Bioinformatics and computational biology involve the use of techniques including applied mathematics, informatics, statistics, computer science, artificial intelligence, chemistry, and biochemistry to solve biological problems usually on the molecular level.
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statistical hypothesis test, or more briefly, hypothesis test, is an algorithm to state the alternative (for or against the hypothesis) which minimizes certain risks.

This article describes the commonly used frequentist treatment of hypothesis testing.
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