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Record Nr. |
UNINA9910704246803321 |
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Titolo |
Assault |
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Pubbl/distr/stampa |
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[Washington, D.C.] : , : Office for Victims of Crime, , [2010?] |
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Descrizione fisica |
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1 online resource (6 unnumbered panels) |
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Collana |
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OVC Help Series for Crime Victims |
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Soggetti |
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Assault and battery - United States |
Victims of violent crimes - Services for - United States |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Title from title screen (viewed February 9, 2016). |
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Nota di bibliografia |
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Includes bibliographical references. |
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2. |
Record Nr. |
UNINA9910877295903321 |
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Autore |
Bartoszyński Robert |
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Titolo |
Probability and statistical inference / / Robert Bartoszynski and Magdalena Niewiadomska-Bugaj |
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Pubbl/distr/stampa |
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Hoboken, N.J. ; ; [Chichester], : Wiley-Interscience, c2008 |
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ISBN |
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9786611203825 |
9781281203823 |
1281203823 |
9780470191590 |
0470191597 |
9780470191583 |
0470191589 |
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Edizione |
[2nd ed.] |
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Descrizione fisica |
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1 online resource (662 p.) |
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Altri autori (Persone) |
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Niewiadomska-BugajMagdalena |
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Disciplina |
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Soggetti |
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Probabilities |
Mathematical statistics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Previous ed.: Chichester: Wiley, 1996. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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PROBABILITY AND STATISTICAL INFERENCE; CONTENTS; Preface; 1 Experiments, Sample Spaces, and Events; 1.1 Introduction; 1.2 Sample Space; 1.3 Algebra of Events; 1.4 Infinite Operations on Events; 2 Probability; 2.1 Introduction; 2.2 Probability as a Frequency; 2.3 Axioms of Probability; 2.4 Consequences of the Axioms; 2.5 Classical Probability; 2.6 Necessity of the Axioms; 2.7 Subjective Probability; 3 Counting; 3.1 Introduction; 3.2 Product Sets, Orderings, and Permutations; 3.3 Binomial Coefficients; 3.4 Extension of Newton's Formula; 3.5 Multinomial Coefficients; 4 Conditional Probability |
Independence4.1 Introduction; 4.2 Conditional Probability; 4.3 Partitions; Total Probability Formula; 4.4 Bayes' Formula; 4.5 Independence; 4.6 Exchangeability; Conditional Independence; 5 Markov Chains; 5.1 Introduction and Basic Definitions; 5.2 Definition of a Markov Chain; 5.3 n-Step Transition Probabilities; 5.4 The Ergodic Theorem; 5.5 Absorption Probabilities; 6 Random Variables: Univariate Case; 6.1 Introduction; 6.2 Distributions of Random Variables; 6.3 Discrete and Continuous Random Variables; 6.4 Functions of Random Variables; 6.5 Survival and Hazard Functions |
7 Random Variables: Multivariate Case7.1 Bivariate Distributions; 7.2 Marginal Distributions; Independence; 7.3 Conditional Distributions; 7.4 Bivariate Transformations; 7.5 Multidimensional Distributions; 8 Expectation; 8.1 Introduction; 8.2 Expected Value; 8.3 Expectation as an Integral; 8.4 Properties of Expectation; 8.5 Moments; 8.6 Variance; 8.7 Conditional Expectation; 8.8 Inequalities; 9 Selected Families of Distributions; 9.1 Bernoulli Trials and Related Distributions; 9.2 Hypergeometric Distribution; 9.3 Poisson Distribution and Poisson Process |
9.4 Exponential, Gamma and Related Distributions9.5 Normal Distribution; 9.6 Beta Distribution; 10 Random Samples; 10.1 Statistics and their Distributions; 10.2 Distributions Related to Normal; 10.3 Order Statistics; 10.4 Generating Random Samples; 10.5 Convergence; 11.5 Sampling; 10.6 Central Limit Theorem; 11 Introduction to Statistical Inference; 11.1 Overview; 11.2 Descriptive Statistics; 11.3 Basic Model; 11.4 Bayesian Statistics; 11.6 Measurement Scales; 12 Estimation; 12.1 Introduction; 12.2 Consistency; 12.3 Loss, Risk, and Admissibility; 12.4 Efficiency |
12.5 Methods of Obtaining Estimators12.6 Sufficiency; 12.7 Interval Estimation; 13 Testing Statistical Hypotheses; 13.1 Introduction; 13.2 Intuitive Background; 13.3 Most Powerful Tests; 13.4 Uniformly Most Powerful Tests; 13.5 Unbiased Tests; 13.6 Generalized Likelihood Ratio Tests; 13.7 Conditional Tests; 13.8 Tests and Confidence Intervals; 13.9 Review of Tests for Normal Distributions; 13.10 Monte Carlo, Bootstrap, and Permutation Tests; 14 Linear Models; 14.1 Introduction; 14.2 Regression of the First and Second Kind; 14.3 Distributional Assumptions |
14.4 Linear Regression in the Normal Case |
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Sommario/riassunto |
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Now updated in a valuable new edition-this user-friendly book focuses on understanding the ""why"" of mathematical statistics Probability and Statistical Inference, Second Edition introduces key probability and statis-tical concepts through non-trivial, real-world examples and promotes the developmentof intuition rather than simple application. With its coverage of the recent advancements in computer-intensive methods, this update successfully provides the comp-rehensive tools needed to develop a broad understanding of the theory of statisticsand |
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its probabilistic foundations. This outstandi |
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