Models for Probability and Statistical Inference – Theory and Applications
Models for Probability and Statistical InferenceTheory and Applications\nAuthor(s): James H. Stapleton\nFormat: Hardback\nPublisher: John Wiley & Sons Inc, United States\nImprint: Wiley-Interscience\nISBN-13: 9780470073728, 978-0470073728\nSynopsis\nThis concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers\n Models for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping.\n Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and ran.
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