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La statistique - considérée comme l'ensemble des méthodes qui ont pour but de recueillir et d'analyser des données relatives à des groupes d'individus ou d'objets - joue un rôle essentiel dans de très nombreuses disciplines. Tel est le cas, entre autres, pour les sciences du vivant : biologie, agronomie, écologie, etc. Les deux tomes de Statistique théorique et appliquée ont précisément pour objectif de permettre aux scientifiques de disciplines très variées, en particulier les sciences du vivant, d'utiliser au mieux les méthodes statistiques classiques, sans en négliger ni les fondements ni les limites. L'objet du tome 1 est la présentation des notions de base de statistique descriptive (à une et à deux dimensions), de statistique théorique (à une et à deux dimensions également), et d'inférence statistique (distributions d'échantillonnage, problèmes d'estimation et tests d'hypothèses). Cet ouvrage est conçu de manière à être à la fois un manuel et un livre de référence. A cette fin, il comporte une documentation détaillée, dont plus de 350 références bibliographiques, des tables, et divers index (index bibliographique, index des traductions anglaises, index des matières et index des symboles). Son utilisation comme manuel est facilitée par la définition de différents plans de lecture, clairement indiqués tout au long du texte, et par la présence de nombreux exemples et exercices, accompagnés de leurs solutions. Des informations complémentaires sont présentées dans un site web. Quatrième de couverture.

Mathematische statistiek --- Statistique mathématique --- Mathematical statistics --- Méthode statistique --- Statistical methods --- Statistique mathématique --- Statistique mathématique. --- Analyse de variance. --- Analysis of variance --- Analyse de covariance. --- Analysis of covariance --- Statistics as Topic --- Statistics as Topic. --- Probabilités. --- Statistics --- data collection --- Mathematical statistics. --- Statistique --- Distribution (théorie des probabilités) --- Probability --- Probabilities

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The analysis of variance (ANOYA) models have become one of the most widely used tools of modern statistics for analyzing multifactor data. The ANOYA models provide versatile statistical tools for studying the relationship between a dependent variable and one or more independent variables. The ANOYA mod­ els are employed to determine whether different variables interact and which factors or factor combinations are most important. They are appealing because they provide a conceptually simple technique for investigating statistical rela­ tionships among different independent variables known as factors. Currently there are several texts and monographs available on the sub­ ject. However, some of them such as those of Scheffe (1959) and Fisher and McDonald (1978), are written for mathematically advanced readers, requiring a good background in calculus, matrix algebra, and statistical theory; whereas others such as Guenther (1964), Huitson (1971), and Dunn and Clark (1987), although they assume only a background in elementary algebra and statistics, treat the subject somewhat scantily and provide only a superficial discussion of the random and mixed effects analysis of variance.

Analysis of variance --- 519.233.4 --- #ABIB:astp --- ANOVA (Analysis of variance) --- Variance analysis --- Mathematical statistics --- Experimental design --- Variance analysis. Covariance analysis --- 519.233.4 Variance analysis. Covariance analysis --- Applied mathematics. --- Engineering mathematics. --- Probabilities. --- Statistics . --- Mathematical analysis. --- Analysis (Mathematics). --- Applications of Mathematics. --- Probability Theory and Stochastic Processes. --- Statistical Theory and Methods. --- Analysis. --- 517.1 Mathematical analysis --- Mathematical analysis --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Risk --- Engineering --- Engineering analysis

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Agriculture --- Statistics --- Statistique --- Statistical methods --- Méthodes statistiques --- 519.2 --- 57.087.1 --- 57.087.1 Biometry. Statistical study and treatment of biological data --- Biometry. Statistical study and treatment of biological data --- 519.2 Probability. Mathematical statistics --- Probability. Mathematical statistics --- $ PDMC --- Statistics [ from old catalog] --- Statistical methods [from old catalog] --- Basic Sciences. Statistics --- Statistical methods. --- Statistics (General). --- Agronomy --- Mathematical statistics --- Statistics. --- Statistique mathématique. --- Probabilités. --- Analyse de variance. --- Analyse de covariance. --- Analyse de régression. --- Statistique. --- AA / International- internationaal --- 300 --- 305.0 --- Algemene statistische naslagwerken. --- Toegepaste econometrie en statistiek (algemene naslagwerken). Statistische onderzoekingen en studiën. --- Algemene statistische naslagwerken --- Toegepaste econometrie en statistiek (algemene naslagwerken). Statistische onderzoekingen en studiën --- Statistique mathématique --- Méthodes statistiques --- Agriculture - Méthodes statistiques --- Statistics - Statistical methods [from old catalog]

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Encompassing both introductory and more advanced research material, these notes deal with the author's contributions to stochastic processes and focus on Brownian motion processes and its derivative white noise.Originally published in 1970.The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.

Stationary processes --- Stationary processes. --- Stochastic processes --- 519.216 --- 519.216 Stochastic processes in general. Prediction theory. Stopping times. Martingales --- Stochastic processes in general. Prediction theory. Stopping times. Martingales --- Bochner integral. --- Bochner's theorem. --- Bounded operator. --- Bounded variation. --- Brownian motion. --- Characteristic exponent. --- Characteristic function (probability theory). --- Complexification. --- Compound Poisson process. --- Computation. --- Conditional expectation. --- Continuous function (set theory). --- Continuous function. --- Continuous linear operator. --- Convergence of random variables. --- Coset. --- Covariance function. --- Cyclic subspace. --- Cylinder set. --- Degrees of freedom (statistics). --- Derivative. --- Differential equation. --- Dimension (vector space). --- Dirac delta function. --- Discrete spectrum. --- Distribution function. --- Dual space. --- Eigenfunction. --- Equation. --- Existential quantification. --- Exponential distribution. --- Exponential function. --- Finite difference. --- Fourier series. --- Fourier transform. --- Function (mathematics). --- Function space. --- Gaussian measure. --- Gaussian process. --- Harmonic analysis. --- Hermite polynomials. --- Hilbert space. --- Homeomorphism. --- Independence (probability theory). --- Independent and identically distributed random variables. --- Indicator function. --- Infinitesimal generator (stochastic processes). --- Integral equation. --- Isometry. --- Joint probability distribution. --- Langevin equation. --- Lebesgue measure. --- Lie algebra. --- Limit superior and limit inferior. --- Linear combination. --- Linear function. --- Linear interpolation. --- Linear subspace. --- Mean squared error. --- Measure (mathematics). --- Monotonic function. --- Normal distribution. --- Normal subgroup. --- Nuclear space. --- One-parameter group. --- Orthogonality. --- Orthogonalization. --- Parameter. --- Poisson point process. --- Polynomial. --- Probability distribution. --- Probability measure. --- Probability space. --- Probability. --- Projective linear group. --- Radon–Nikodym theorem. --- Random function. --- Random variable. --- Reproducing kernel Hilbert space. --- Self-adjoint operator. --- Self-adjoint. --- Semigroup. --- Shift operator. --- Special case. --- Stable process. --- Stationary process. --- Stochastic differential equation. --- Stochastic process. --- Stochastic. --- Subgroup. --- Summation. --- Symmetrization. --- Theorem. --- Transformation semigroup. --- Unitary operator. --- Unitary representation. --- Unitary transformation. --- Variance. --- White noise. --- Zero element.

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519.2 --- Statistics --- #KVHB:Statistiek --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- 519.2 Probability. Mathematical statistics --- Probability. Mathematical statistics --- Statistics. --- Biometry --- Statistics as Topic --- 57.087.1 --- 57.087.1 Biometry. Statistical study and treatment of biological data --- Biometry. Statistical study and treatment of biological data --- Area Analysis --- Correlation Studies --- Correlation Study --- Correlation of Data --- Data Analysis --- Estimation Technics --- Estimation Techniques --- Indirect Estimation Technics --- Indirect Estimation Techniques --- Multiple Classification Analysis --- Service Statistics --- Statistical Study --- Statistics, Service --- Tables and Charts as Topic --- Analyses, Area --- Analyses, Data --- Analyses, Multiple Classification --- Analysis, Data --- Analysis, Multiple Classification --- Area Analyses --- Classification Analyses, Multiple --- Classification Analysis, Multiple --- Data Analyses --- Data Correlation --- Data Correlations --- Estimation Technic, Indirect --- Estimation Technics, Indirect --- Estimation Technique --- Estimation Technique, Indirect --- Estimation Techniques, Indirect --- Indirect Estimation Technic --- Indirect Estimation Technique --- Multiple Classification Analyses --- Statistical Studies --- Studies, Correlation --- Studies, Statistical --- Study, Correlation --- Study, Statistical --- Technic, Indirect Estimation --- Technics, Estimation --- Technics, Indirect Estimation --- Technique, Estimation --- Technique, Indirect Estimation --- Techniques, Estimation --- Techniques, Indirect Estimation --- Anthropology, Physical --- Statistiek --- #ECO:01.02:economie theorie geschiedenis denken --- #ECO:01.15:economie statistiek evolutie previsie --- 519.22 --- 519.22 Statistical theory. Statistical models. Mathematical statistics in general --- Statistical theory. Statistical models. Mathematical statistics in general --- #WPLT:dd.Prof.F.Symons --- sociale wetenschappen --- statistiek --- Mathematical statistics --- Statistics as Topic. --- Agriculture --- Biology --- ZV Statistics --- Statistique mathématique --- Mathematical statistics. --- Statistique mathématique --- Agriculture - Statistics --- Biology - Statistics --- CLASSIFICATION IN STATISTICS --- EXPERIMENTS ANALYSIS IN STATISTICS[FACTORIAL-] --- VARIANCE[ANALYSIS OF] --- COVARIANCE[ANALYSIS OF] --- REGRESSION[MULTIPLE-] --- REGRESSION[CURVILINEAR-] --- SAMPLING TECHNIQUES[STATISTICAL-] --- REGRESSION AND CORRELATION --- SAMPLING FROM BINOMIAL DISTRIBUTION --- STATISTICS[NON PARAMETRIC-] --- DISTRIBUTIONS[PROBABILITY-] --- SAMPLING DESIGN --- EXPERIMENTS ANALYSIS IN STATISTICS --- SAMPLING THEORY --- SAMPLING DISTRIBUTION --- STATISTICAL HYPOTHESES TESTING --- Biostatistique