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, in biology
biometrics, also known as biostatistics or biometry, in biology, the development and application of statistical and mathematical methods to the analysis of data resulting from biological observations and phenomena. Biometrics is used in clinical trials evaluating the relative effectiveness of different therapies; in genetic and genomic studies of the makeup of nucleotide sequences in an organism; in epidemiological studies of the patterns, causes, and control of diseases and public health problems; and in many other areas of biological research. Although the terms biometry and biostatistics are often used interchangeably, the former is now more frequently applied to agricultural and biological applications while the latter is more frequently applied to medical applications. Biometrics played a key role in the development of modern biology. The rediscovery of Gregor Mendel's work in the early 1900s led to conceptual gaps between the proponents of genetics and evolutionary Darwinism. By the 1930s, after vigorous debate, models built on statistical reasoning had resolved most of the differences to produce a coherent biology.
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The following article is from The Great Soviet Encyclopedia (1979). It might be outdated or ideologically biased.



a branch of biology concerned with planning and interpreting the results of quantitative experiments and observations by the methods of mathematical statistics. In conducting biological experiments and observations an investigator always has to deal with quantitative variations in the frequency of occurrence or degree of manifestation of different characteristics and properties. Hence, without special statistical analysis it is usually impossible to determine what the possible limits of random variations may be and whether the observed differences between the experimental versions are accidental or significant. Mathematical statistical methods as used in biology are sometimes developed without reference to biological research. More often, however, they are related to the problems that arise in biology, agriculture, and medicine.

Biometry as an independent discipline developed at the end of the 19th century as a result of the work of the Englishman F. Galton, who made a major contribution to the creation of correlation and regression analysis, and K. Pearson, the founder of the most important school of biometry. Pearson analyzed in detail the main types of distributions found in biology. He developed the theory of correlation and proposed one of the best-known statistical methods, the “chisquare” criterion. The methodology of modern biometry was developed by R. A. Fisher (England), who founded his own school of biometry. Fisher was the first to show that planning experiments and observations and interpreting the results are two inseparable aspects of statistical analysis. He laid the foundations for the theory of experiment planning and proposed several efficient statistical methods (chiefly, dispersion [variance] analysis) which naturally emerge from the peculiarities of biological experiments. He also elaborated the theory of small samples first advanced by the English scientist Student (W. Gosset). The Russian scientists V. I. Romanovskii, A. A. Sapegin, Iu. A. Filipchenko, S. S. Chetverikov, and others played an important part in spreading biometric ideas and methods.

The use of mathematical statistical methods in biology essentially involves choosing some statistical model, checking to see that it conforms to the experimental data, and analyzing the statistical and biological results that it produces. The choice of a particular model is largely determined by the biological nature of the experiment. Any model contains a number of assumptions that must be tested in the experiment: for instance, the randomness of the choice of objects from a general set and, very commonly, the specific type of distribution of the random quantity to be investigated. The design of experiments has become an independent branch of biometry, which has several methods of effectively staging experiments at its disposal (such as different systems of dispersion analysis, sequential analysis, and design of screening experiments). These methods are of value in reducing the scope of an experiment to obtain the same amount of information. Three main statistical problems arise in interpreting the results of experiments and observations: (1) evaluation of the parameters of distribution—mean, dispersion, and so on (for example, establishing the limits of random variations in the number of patients who show improvement when treated with some drug under trial); (2) comparison of the parameters of different samples (for example, determining whether the difference between average yields of wheat varieties under study are accidental or significant); (3) detection of statistical relations—correlation, regression (for example, study of the correlation between the size or mass of different animal organs or study of the relationship between the frequency of cell injury and dose of ionizing radiation). The methods of multidimensional statistics are particularly useful in solving experimental problems because they make it possible to evaluate simultaneously the effect of several different factors and the interaction between them. These methods are being increasingly used to solve problems in taxonomy. Nonparametric methods without assumptions concerning the nature of the distribution of random quantities have become popular, but they are not as effective as parametric methods. Because of practical needs intensive efforts are being made to develop methods for studying heredity, sampling methods, and methods for studying dynamic processes (temporal series).

Articles on biometry are published in the journals Biometrika (London, 1901—), Biometrics (Atlanta, 1945—), and Biometrische Zeitschrift (Berlin, 1959—) and in various biological, agricultural, and medical journals.


Bailey, N. Statisticheskie metody ν biologii. Moscow, 1963. (Translated from English.)
Rokitskii, P. F. Biologicheskaia statistika, 2nd ed. Minsk, 1967.
Snedecor, G. W. Statisticheskie metody ν primenenii k issledovaniiam ν sel’skom khoziaistve i biologii. Moscow, 1961. (Translated from English.)
Urbakh, V. Iu. Biometricheskie metody, 2nd ed. Moscow, 1964.
Finney, D. J. Primenenie statistiki ν opytnom dele. Moscow, 1957. (Translated from English.)
Finney, D. J. Vvedenie ν teoriiu planirovaniia eksperimentov. Moscow, 1970. (Translated from English.)
Fisher, R. A. Statisticheskie metody dlia issledovatelei. Moscow, 1958. (Translated from English.)
Hill, B. Osnovy meditsinskoi statistiki. Moscow, 1958. (Translated from English.)
Hicks, C. Osnovnye printsipy planirovaniia eksperimenta. Moscow, 1967. (Translated from English.)
Fisher, R. A. The Design of Experiments. Edinburgh-London, 1960.


The Great Soviet Encyclopedia, 3rd Edition (1970-1979). © 2010 The Gale Group, Inc. All rights reserved.


The use of statistics to calculate the average length of time that a human being lives.
McGraw-Hill Dictionary of Scientific & Technical Terms, 6E, Copyright © 2003 by The McGraw-Hill Companies, Inc.


, biometrics
a. the analysis of biological data using mathematical and statistical methods
b. the practice of digitally scanning the physiological or behavioural characteristics of individuals as a means of identification
2. the statistical calculation of the probable duration of human life
Collins Discovery Encyclopedia, 1st edition © HarperCollins Publishers 2005
References in periodicals archive ?
Fetal biometry is the methodology for measuring various aspects of fetal anatomy and growth.1 Fetal growth is the time dependent changes in the fetal body dimensions throughout the pregnancy.
(1998) used ultrasonic biometry for the measurement of different intraocular distances and reported average axial length (20.91 [+ or -] 0.53), anterior chamber depth (5.07 [+ or -] 0.361) and lens thickness (7.77 [+ or -] 0.23) which were larger than our findings.
The results in our study also showed that combination of different parameters of ultrasound biometry when combined with different doppler parameters gives better accuracy and can also predict the severity of the condition.
Refractive error and ocular biometry in Jordanian adults.
Intraobserver and interobserver reproducibility of fetal biometry. Ultrasound Obstet Gynecol 2004;24(6):654-658.
KEY WORDS: Ocular Biometry; Intra Ocular Pressure; Intra Ocular Lens; Cataract; Pseudoexfoliation Syndrome.
I also tend to have less confidence in fetal biometry in this population, particularly in the third trimester.
"Whether they are evaluating the fetal heart in real time or analyzing fetal biometry to assess growth and well-being, it's essential for the clinician to be able to view high quality, clear ultrasound images," said Anne LeGrand, senior vice president, Ultrasound, for Philips Healthcare.
In addition to the surgical challenges of operating on a very large eyeball, there are many technical challenges like getting all the complex calculations required for the lens implant, a process called biometry.
She went on to receive her MA in Biometry and Statistics from SUNY, Albanys School of Public Health, Albany, NY.
The foreword describes how ICIAP has become the international conference that joins together the Italian and international communities of researchers working on image processing, pattern recognition, computer vision, and multimedia; and it also explains that the proceedings of the 2007 conference (Modena, Italy) are available digitally, but a deliberate decision was made to print a book (there's no CD) because the format continues to be useful in the digital age and "...Books attest to the history of culture, books are culture and books cannot be replaced by digital access." Approximately 130 oral and poster presentations (from 41 countries) are arranged in sections on biometry, theory, industrial applications, surveillance and security, multimedia, and medical imaging.