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Probability and Statistics (4th Edition) The revision of this well-respected text presents a balanced approach of the classical and Bayesian methods and now includes a chapter on simulation (including Markov chain Monte Carlo and the Bootstrap), coverage of residual analysis in linear models, and many examples using real data. Calculus is assumed as a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus. |
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Probability and Statistics for Engineering and the SciencesJay L. DevoreBooks |
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Probability and Statistics with Reliability, Queueing, and Computer Science Applications, 2nd EditionKishor Shridharbhai TrivediBooks |
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Basic Probability Theory (Dover Books on Mathematics)Robert B. AshBooks |
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Applied Statistics and Probability for Engineers Douglas C. Montgomery
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A Modern Introduction to Probability and Statistics F.M. Dekking
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Probability and Statistics for Engineers and Scientists (9th Edition) Ronald E. Walpole
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Schaum's Outline of Probability and Statistics, 3rd Ed. (Schaum's Outline Series)
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CK-12 Advanced Probability and Statistics eBookCK-12 FoundationKindle Store |
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