05252nam 22006134a 450 991082992710332120230721030208.01-281-22157-097866112215770-470-18341-10-470-18340-3(CKB)1000000000377286(EBL)331445(OCoLC)437198702(SSID)ssj0000204124(PQKBManifestationID)11175454(PQKBTitleCode)TC0000204124(PQKBWorkID)10187891(PQKB)10084169(MiAaPQ)EBC331445(EXLCZ)99100000000037728620070330d2008 uy 0engur|n|---|||||txtccrModels for probability and statistical inference[electronic resource] theory and applications /James H. StapletonHoboken, N.J. Wiley-Intersciencec20081 online resource (466 p.)Wiley series in probability and statisticsDescription based upon print version of record.0-470-07372-1 Includes bibliographical references (p. 378-380) and index.Models for Probability and Statistical Inference; Contents; Preface; 1. Discrete Probability Models; 1.1. Introduction; 1.2. Sample Spaces, Events, and Probability Measures; 1.3. Conditional Probability and Independence; 1.4. Random Variables; 1.5. Expectation; 1.6. The Variance; 1.7. Covariance and Correlation; 2. Special Discrete Distributions; 2.1. Introduction; 2.2. The Binomial Distribution; 2.3. The Hypergeometric Distribution; 2.4. The Geometric and Negative Binomial Distributions; 2.5. The Poisson Distribution; 3. Continuous Random Variables; 3.1. Introduction3.2. Continuous Random Variables3.3. Expected Values and Variances for Continuous Random Variables; 3.4. Transformations of Random Variables; 3.5. Joint Densities; 3.6. Distributions of Functions of Continuous Random Variables; 4. Special Continuous Distributions; 4.1. Introduction; 4.2. The Normal Distribution; 4.3. The Gamma Distribution; 5. Conditional Distributions; 5.1. Introduction; 5.2. Conditional Expectations for Discrete Random Variables; 5.3. Conditional Densities and Expectations for Continuous Random Variables; 6. Moment Generating Functions and Limit Theory; 6.1. Introduction6.2. Moment Generating Functions6.3. Convergence in Probability and in Distribution and the Weak Law of Large Numbers; 6.4. The Central Limit Theorem; 7. Estimation; 7.1. Introduction; 7.2. Point Estimation; 7.3. The Method of Moments; 7.4. Maximum Likelihood; 7.5. Consistency; 7.6. The δ-Method; 7.7. Confidence Intervals; 7.8. Fisher Information, Cramér-Rao Bound and Asymptotic Normality of MLEs; 7.9. Sufficiency; 8. Testing of Hypotheses; 8.1. Introduction; 8.2. The Neyman-Pearson Lemma; 8.3. The Likelihood Ratio Test8.4. The p-Value and the Relationship between Tests of Hypotheses and Confidence Intervals9. The Multivariate Normal, Chi-Square, t, and F Distributions; 9.1. Introduction; 9.2. The Multivariate Normal Distribution; 9.3. The Central and Noncentral Chi-Square Distributions; 9.4. Student's t-Distribution; 9.5. The F-Distribution; 10. Nonparametric Statistics; 10.1. Introduction; 10.2. The Wilcoxon Test and Estimator; 10.3. One-Sample Methods; 10.4. The Kolmogorov-Smirnov Tests; 11. Linear Statistical Models; 11.1. Introduction; 11.2. The Principle of Least Squares; 11.3. Linear Models11.4. F-Tests for H(0): θ = β(1)X(1) + · · · + β(k)X(k) V(0), a Subspace of V11.5. Two-Way Analysis of Variance; 12. Frequency Data; 12.1. Introduction; 12.2. Confidence Intervals on Binomial and Poisson Parameters; 12.3. Logistic Regression; 12.4. Two-Way Frequency Tables; 12.5. Chi-Square Goodness-of-Fit Tests; 13. Miscellaneous Topics; 13.1. Introduction; 13.2. Survival Analysis; 13.3. Bootstrapping; 13.4. Bayesian Statistics; 13.5. Sampling; References; Appendix; Answers to Selected Problems; IndexThis concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readersModels 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.Ideal as a textbook for a two-semeWiley series in probability and statistics.ProbabilitiesMathematical modelsProbabilitiesIndustrial applicationsProbabilitiesMathematical models.ProbabilitiesIndustrial applications.519.2Stapleton James H.1931-105221MiAaPQMiAaPQMiAaPQBOOK9910829927103321Models for probability and statistical inference3935843UNINA00997nam0 22002771i 450 UON0001139020231205101935.24420020107d1973 |0itac50 barusSU|||| 1||||Samoanskij jazykV.D. ArakinMoskvaNauka197385 p.20 cm001UON000111122001 Jazyki Narodov Azii i AfrikiLINGUA SAMOANAMANUALIUONC004151FIRUMoskvaUONL003152POL IIPOLINESIA - LINGUISTICAAARAKINV. D.UONV008832639618Akademija Nauk SSSRUONV247334650ITSOL20241213RICASIBA - SISTEMA BIBLIOTECARIO DI ATENEOUONSIUON00011390SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI POL II 003 SI SA 75884 5 003 Samoanskij jazyk1178902UNIOR