1.

Record Nr.

UNINA9910704246803321

Titolo

Assault

Pubbl/distr/stampa

[Washington, D.C.] : , : Office for Victims of Crime, , [2010?]

Descrizione fisica

1 online resource (6 unnumbered panels)

Collana

OVC Help Series for Crime Victims

Soggetti

Assault and battery - United States

Victims of violent crimes - Services for - United States

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Title from title screen (viewed February 9, 2016).

Nota di bibliografia

Includes bibliographical references.

2.

Record Nr.

UNINA9910877295903321

Autore

Bartoszyński Robert

Titolo

Probability and statistical inference / / Robert Bartoszynski and Magdalena Niewiadomska-Bugaj

Pubbl/distr/stampa

Hoboken, N.J. ; ; [Chichester], : Wiley-Interscience, c2008

ISBN

9786611203825

9781281203823

1281203823

9780470191590

0470191597

9780470191583

0470191589

Edizione

[2nd ed.]

Descrizione fisica

1 online resource (662 p.)

Altri autori (Persone)

Niewiadomska-BugajMagdalena

Disciplina

519

519.54

Soggetti

Probabilities

Mathematical statistics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa



Livello bibliografico

Monografia

Note generali

Previous ed.: Chichester: Wiley, 1996.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

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

Sommario/riassunto

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



its probabilistic foundations. This outstandi