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Cet ouvrage expose les fondements théoriques des méthodes classiques de la statistique (estimation et tests) ainsi que des approches introduites plus récemment. Les premiers chapitres sont consacrés aux notions de la théorie des probabilités, nécessaires à la statistique. Puis sont développés les tests et méthodes d'estimation dans les situations paramétriques et non paramétriques. Les modèles de base de la régression sont traités en fin d'ouvrage. Chaque chapitre est accompagné d'exemples concrets, mais aussi d'exercices - plus de 150 au total - dont les corrigés ont été intégrés dans cette deuxième édition. La présentation témoigne d'un réel souci pédagogique de l'auteur qui bénéficie d'une vaste expérience d'enseignement auprès de publics très variés. Les résultats exposés sont, autant que possible, replacés dans la perspective de leur utilité pratique. Le niveau mathématique requis rend ce livre accessible aux étudiants de premier cycle universitaire et aux chercheurs dans les divers domaines des sciences appliquées. Il sera donc utile aux étudiants devant aborder les aspects théoriques de la statistique ou aux utilisateurs, pour les assurer du choix judicieux des méthodes qu'ils emploient.

Statistics. --- Statistical Theory and Methods. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law. --- Mathematical statistics. --- Statistique --- Statistique mathématique --- Statistics as Topic

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Arguably the most intricate dynamic object in the universe, the human brain is an unsounded source of wonder for the scienti?c community. The primary aim of this book is to provide both students and established - vestigators in the growing area of neuroscience with an appreciation of the roles that mathematics may play in helping to understand this en- maticorgan. Alongwithdiscussionsofresultsobtainedbytheneuroscience community, emphasis is placed on suggesting fruitful research problems for those planning to embark on mathematical studies in neuroscience. To make the overall perspectives understandable to philosophers and psychologists, essential features of the discussions are presented in ordinary English, with more detailed mathematical comments in appendices and footnotes. Although it attempts to maintain both clarity and biological relevance, this is not a text on the anatomy of nerve systems; thus readers should bring some knowledge of neurophysiology through other courses, associated studies, or laboratory research. It is a guiding theme throughout the book that the brain is organized into several quite di?erent levels of dynamic activity. As will be seen, these levels are hierarchically structured, beginning with the molecular dynamics ofintrinsicmembraneproteinsandproceedingupward,throughtheswit- ing properties of active membrane patches and synapses, the emergence of impulses on active ?bers, overall properties of individual neurons, and the growth of functional assemblies of interacting neurons, to the global - namics of a brain. At each level of description, reality turns di?erent facets of her mystery to us, and diverse phenomena make their contributions to the brain’s collective behavior.

Physiology of nerves and sense organs --- Computer. Automation --- Mathematics --- #PBIB:2004.3 --- Neurosciences --- Mathematical models. --- Life sciences. --- Neurosciences. --- Neurobiology. --- Biomathematics. --- Statistics. --- Life Sciences. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Mathematical and Computational Biology. --- Neural sciences --- Neurological sciences --- Neuroscience --- Medical sciences --- Nervous system --- Mathematical models --- Statistics . --- Biology --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics

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Hierarchy is a form of organisation of complex systems that rely on or produce a strong differentiation in capacity (power and size) between the parts of the system. It is frequently observed within the natural living world as well as in social institutions. According to the authors, hierarchy results from random processes, follows an intentional design, or is the result of the organisation which ensures an optimal circulation of energy for information. This book reviews ancient and modern representations and explanations of hierarchies, and compares their relevance in a variety of fields, such as language, societies, cities, and living species. It throws light on concepts and models such as scaling laws, fractals and self-organisation that are fundamental in the dynamics and morphology of complex systems. At a time when networks are celebrated for their efficiency, flexibility and better social acceptance, much can be learned about the persistent universality and adaptability of hierarchies, and from the analogies and differences between biological and social organisation and processes. This book addresses a wide audience of biologists and social scientists, as well as managers and executives in a variety of institutions.

Hierarchies. --- Order --- Geografie --- Sociale en economische geografie --- Algemeen. --- Social stratification --- Organization. --- Social sciences --- Systems theory. --- Social sciences. --- Genetic epistemology. --- Statistics. --- Methodology of the Social Sciences. --- Systems Theory, Control. --- Social Sciences, general. --- Epistemology. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Methodology. --- System theory. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Developmental psychology --- Knowledge, Theory of --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Civilization --- Organisation --- Management --- Systems, Theory of --- Systems science --- Science --- Philosophy --- Planning. --- Statistics . --- Epistemology --- Theory of knowledge --- Psychology --- Creation (Literary, artistic, etc.) --- Executive ability --- Organization --- Social sciences (general) --- Biomathematics. Biometry. Biostatistics --- Environmental planning --- Linguistics --- medische statistiek --- ruimtelijke ordening --- biostatistiek --- sociale wetenschappen --- epistomologie --- linguïstiek --- biometrie --- kennisleer

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Statistical Tools for Nonlinear Regression, (Second Edition), presents methods for analyzing data using parametric nonlinear regression models. The new edition has been expanded to include binomial, multinomial and Poisson non-linear models. Using examples from experiments in agronomy and biochemistry, it shows how to apply these methods. It concentrates on presenting the methods in an intuitive way rather than developing the theoretical backgrounds. The examples are analyzed with the free software nls2 updated to deal with the new models included in the second edition. The nls2 package is implemented in S-Plus and R. Its main advantages are to make the model building, estimation and validation tasks, easy to do. More precisely, Complex models can be easily described using a symbolic syntax. The regression function as well as the variance function can be defined explicitly as functions of independent variables and of unknown parameters or they can be defined as the solution to a system of differential equations. Moreover, constraints on the parameters can easily be added to the model. It is thus possible to test nested hypotheses and to compare several data sets. Several additional tools are included in the package for calculating confidence regions for functions of parameters or calibration intervals, using classical methodology or bootstrap. Some graphical tools are proposed for visualizing the fitted curves, the residuals, the confidence regions, and the numerical estimation procedure. This book is aimed at scientists who are not familiar with statistical theory, but have a basic knowledge of statistical concepts. It includes methods based on classical nonlinear regression theory and more modern methods, such as bootstrap, which have proved effective in practice. The additional chapters of the second edition assume some practical experience in data analysis using generalized linear models. The book will be of interest both for practitioners as a guide and a reference book, and for students, as a tutorial book. Sylvie Huet and Emmanuel Jolivet are senior researchers and Annie Bouvier is computing engineer at INRA, National Institute of Agronomical Research, France; Marie-Anne Poursat is associate professor of statistics at the University Paris XI.

Regression analysis. --- Nonlinear theories. --- Parameter estimation. --- 57.087.1 --- 519.233.5 --- #SBIB:303H520 --- #SBIB:303H61 --- 519.233.5 Correlation analysis. Regression analysis --- Correlation analysis. Regression analysis --- 57.087.1 Biometry. Statistical study and treatment of biological data --- Biometry. Statistical study and treatment of biological data --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Wiskundige methoden en technieken --- Statistics. --- Statistical Theory and Methods. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Nonlinear theories --- Parameter estimation --- Regression analysis --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Estimation theory --- Stochastic systems --- Nonlinear problems --- Nonlinearity (Mathematics) --- Calculus --- Mathematical analysis --- Mathematical physics --- Mathematical statistics. --- Statistics . --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics

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Randomized clinical trials are the gold standard for establishing many clinical practice guidelines and are central to evidence based medicine. Obtaining the best evidence through clinical trials must be done within the boundaries of rigorous science and ethical principles. One fundamental principle is that trials should not continue longer than necessary to reach their objectives. Therefore, trials must be monitored for recruitment progress, quality of data, adherence to patient care or prevention standards, and early evidence of benefit or harm. Frequently, a group of external experts, independent from the investigators and trial sponsor, is charged with this monitoring responsibility, especially for safety and early benefit. This group is referred to by various names, such as a data monitoring committee or a data and safety monitoring board. This book, through a series of case studies presented by many distinguished clinical trial experts, illustrates the complexity of this monitoring process. The editors provide an overview of the process and a summary of a multitude of the lessons learned from the cases presented. This book should be useful to anyone serving on a data and safety monitoring board, or planning to do so, for colleagues in academia, industry and governmental agencies, and for teaching students in biostatistics, epidemiology, clinical trials and medical ethics. No other text has as extensive a collection of cases which provide insight into the many issues, often conflicting, that must be examined before recommendations to continue or discontinue a trial can be made. While depth in statistical methods is not required, some familiarity with statistical design and analysis issues in clinical trials is helpful. The cases cover trials which were terminated early for convincing evidence of benefit, or for harmful effects. Cases with complex issues are also included. This series of cases should provide broad background information for potential monitoring committee members and better prepare them for the challenges that may exist in the trials for which they are responsible. The three editors have contributed two overview chapters as well as several case studies to go along with cases contributed by a distinguished group of colleagues experienced in the design, monitoring and analysis of clinical trials. Dr. David DeMets is currently Professor and Chair, Department of Biostatistics and Medical Informatics at the University of Wisconsin-Madison. He is past president of the Eastern North American Region (ENAR) of the International Biometric Society, a past member of the Board of Directors of the American Statistical Association and an elected Fellow. He recently received the Robert Gordon Lectureship Award, given by the National Institutes of Health, for significant contributions to the field of clinical trials. Dr. Curt Furberg, is currently Professor (and former Chair) of the Department of Public Health Sciences at Wake Forest University. Previously, he was Head of the Clinical Trials Branch and Associate Director of the Clinical Applications and Prevention Program at the National Heart, Lung, and Blood Institute. Dr. Lawrence Friedman is a former Director of the Division of Epidemiology and Clinical Applications and a former Assistant Director for Ethics and Clinical Research at the National Heart, Lung, and Blood Institute. All three are past presidents of the Society of Clinical Trials. The editors have collaborated previously as coauthors of a text: the Fundamentals of Clinical Trials.

Biomathematics. Biometry. Biostatistics --- medische statistiek --- biostatistiek --- Clinical Trials --- Automatic Data Processing. --- Clinical trials --- Etudes cliniques --- Case Reports. --- Data processing. --- Case studies. --- Informatique --- Cas, Etudes de --- Clinical trials - Data processing. --- Controlled Clinical Trials as Topic --- Research --- Professional Staff Committees --- Clinical Trials as Topic --- Quality Assurance, Health Care --- Science --- Natural Science Disciplines --- Health Care Quality, Access, and Evaluation --- Epidemiologic Study Characteristics as Topic --- Evaluation Studies as Topic --- Health Care --- Epidemiologic Methods --- Disciplines and Occupations --- Health Care Evaluation Mechanisms --- Investigative Techniques --- Quality of Health Care --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Public Health --- Environment and Public Health --- Randomized Controlled Trials as Topic --- Biomedical Research --- Clinical Trials Data Monitoring Committees --- Mathematics --- Medicine --- Physical Sciences & Mathematics --- Health & Biological Sciences --- Mathematical Statistics --- Medical Research --- Data processing --- Statistics. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Statistics .