Titlebook: Introduction to Biometry; Pierre Jolicoeur Book 1999 Springer Science+Business Media New York 1999 ANOVA.Fisher‘s linear discriminant.Norm

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Introduction,differ from each other in size and shape as well as in their functions, the study of these differences requires statistical methods. Consequently, the word . often considered as a synonym of . However, biometricians generally pay more attention to biological aspects than statisticians would do. For

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Looking at quantitative biological data through scatter diagrams,y important. One of the most useful graphical methods in statistics is the ., in which variable measurements are represented simply by dots dispersed on a surface overlaid by Cartesian coordinate axes (named after the French mathematician René Descartes, 1596–1650). Such coordinate axes are usually

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Frequencies and probabilities,e located in the same class or have the same value. The number of beings or of observations “falling” in that class or possessing that value is then called the . (or .) of that class or of that value. Since the sample is usually spread over several classes, the sum of the frequencies of all classes

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Measures of central tendency and of dispersion,iples: the tendency of observations toward a central value on the one hand, and the dispersion of the same observations about that central value on the other hand. This state of things may be summarized algebraically by a ..where . is the subscript (order number) of the .. observation in a sample, .

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Hypothesis testing and confidence intervals concerning one or two means,and the variance σ.: X ← . (µ.,σ.). However, the methods discussed here will retain their validity in many other cases where the variate X is not normally distributed but can be transformed into another variate Y=g(X) having a normal distribution . (µ.,σ.). In such cases, once the statistical analys