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Biomathematics. Biometry. Biostatistics --- Mathematical statistics --- Medicine --- Médecine --- Research --- Statistical methods. --- Recherche --- Méthodes statistiques --- Statistics as Topic --- Biometry --- methods --- -Clinical sciences --- Medical profession --- Human biology --- Life sciences --- Medical sciences --- Pathology --- Physicians --- -Statistical methods --- -Research --- Médecine --- Méthodes statistiques --- Clinical sciences --- Research&delete& --- Statistical methods --- Health Workforce --- Statistics as Topic - methods

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" Intuitive Biostatistics takes a non-technical, non-quantitative approach to statistics and emphasizes interpretation of statistical results rather than the computational strategies for generating statistical data. This makes the text especially useful for those in health-science fields who have not taken a biostatistics course before. The text is also an excellent resource for professionals in labs, acting as a conceptually oriented and accessible biostatistics guide. With an engaging and conversational tone, Intuitive Biostatistics provides a clear introduction to statistics for undergraduate and graduate students and also serves as a statistics refresher for working scientists. "--

Medicine --- Médecine --- SCIENCE / Life Sciences / General. --- SCIENCE / Life Sciences / Biology / General. --- MEDICAL / Biostatistics. --- Research --- Statistical methods. --- Recherche --- Méthodes statistiques. --- Biometry. --- Biostatistics

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Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting. This book addresses this relatively focused need of an extraordinarily broad range of scientists.

Biology --- Regression analysis. --- Nonlinear theories. --- Curve fitting. --- Fitting, Curve --- Numerical analysis --- Least squares --- Smoothing (Numerical analysis) --- Statistics --- Nonlinear problems --- Nonlinearity (Mathematics) --- Calculus --- Mathematical analysis --- Mathematical physics --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Biological models --- Biomathematics --- Mathematical models. --- Graphic methods

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Cet ouvrage présente les principales méthodes de statistique médicale utilisées dans la pratique quotidienne et dans la littérature théorique. Par une approche claire et synthétique, il aborde de manière détaillée les concepts et les techniques de base tels qu'intervalle de confiance, test d'hypothèse, p-valeur, test t, test x2, corrélation et régression. Il introduit également les tests non paramétriques, la survie, l'analyse de variance à un facteur et des techniques plus poussées telles que la régression linéaire multiple, logistique et non linéaire.L'auteur insiste tout particulièrement sur l'interprétation des résultats, les conditions et situations d'application des méthodes et il met l'accent sur les aspects pratiques. Les sections plus techniques ou avancées sont signalées et peuvent être sautées sans conséquence pour la compréhension de l'ensemble. Des exemples médicaux illustrent la théorie et des exercices résolus en détails figurent en fin de chaque chapitre.

Statistics as Topic --- Biometry --- methods --- WA 950 Theory or methods of medical statistics --- Medicine --- Research --- Statistical methods --- Methods --- Statistics as Topic - methods --- Statistics