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Using R for Bayesian Spatial and Spatio-Temporal Health Modeling provides a major resource for those interested in applying Bayesian methodology in small area health data studies.
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This advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on support with their implementation.
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This innovative textbook and online resource package equips students with the tools needed to develop a working knowledge of finite... Læs mere
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In biostatistical research and courses, practitioners and students often lack a thorough understanding of how to apply statistical methods to synthesize... Læs mere
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Packed with practical advice and real-world examples, this step-by-step guide is an accessible introduction to doing quantitative social research using Microsoft Excel.
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Introduces new graph theory techniques for the analysis and integration of multi-type large data sets) in the life sciences. Discussing... Læs mere
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Linear Models with Python offers up-to-date insight on essential data analysis topics, from estimation, inference, and prediction to missing data, factorial models, and block designs. Numerous examples illustrate how to apply the different methods using Python
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This book is bridging the gap for organisations and individuals who need to learn and use R in a part-time professional context, providing a set of skills to understand the usefulness of graphing, mapping, and modelling in R, using relatable examples throughout.
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John MacInnes takes the fear out of statistics for students, and helps to raise the standards of their quantitative methods skills, by clearly and accessibly introducing all that’s needed to know about using secondary data and working with IBM SPSS Statistics.
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Now in its second edition, this textbook introduces readers to the IBM SPSS Modeler and guides them through data mining processes and relevant statistical methods.
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This book provides a general introduction to Sequential Monte Carlo (SMC) methods, also known as particle filters. Bayesian inference or rare-event problems),... Læs mere