| Description |
1 online resource (646 pages) |
| Series |
Chapman and Hall/CRC Texts in Statistical Science ; v. 22 |
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Chapman and Hall/CRC Texts in Statistical Science
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| Contents |
Cover; Half Title; Title Page; Copyright Page; Contents; Preface; 1. Preliminaries; 1.1 Counting outcomes; Problems; 1.2 Set algebra; Problems; 1.3 Events; 1.4 Functions on a sample space; Problems; 2. Probability; 2.1 Experiments with symmetries; 2.2 The law of large numbers; 2.3 Subjective probability; Problems; 2.4 Probability axioms; Problems; 2.5 Discrete probability spaces; 2.6 Densities; Problems; 2.7 Conditional probability; 2.8 Bayes' theorem; Problems; 3. Random Variables; 3.1 Discrete random variables; Problems; 3.2 Distribution functions; Problems; 3.3 Continuous random variables |
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3.4 Continuous random vectorsProblems; 3.5 Functions of random variables; Problems; 3.6 Conditional distributions; Problems; 3.7 Independence; Problems; 3.8 Exchangeable variables; Problems; 4. Expectations; 4.1 Discrete random variables; 4.2 Continuous random variables; Problems; 4.3 Functions of random variables; Problems; 4.4 Moments; 4.5 Variance; 4.6 Chebyshev and related inequalities; Problems; 4.7 Covariance; 4.8 Correlation; Problems; 4.9 Generating functions; Problems; 4.10 Characteristic functions; 4.11 Multivariate generating functions; Problems; 5. Limit Theorems; 5.1 Convergence |
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5.2 Law of large numbers5.3 The central limit theorem; Problems; 6. Some Parametric Families; 6.1 Bernoulli trials; 6.2 The binomial distribution; Problems; 6.3 Hypergeometric distributions; 6.4 Negative binomial distributions; Problems; 6.5 The Poisson process; Problems; 6.6 Exponential and related distributions; Problems; 6.7 Gamma and beta distributions; Problems; 6.8 Normal distributions; 6.9 Chi-square distributions; Problems; 6.10 Multinomial distributions; 6.11 Exponential families; 6.12 The Cauchy family; Problems; 7. Sampling and Reduction of Data; 7.1 Random sampling |
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7.2 Describing samplesProblems; 7.3 Sampling distributions; 7.4 Sampling distributions of sample moments; 7.5 Sampling normal populations; Problems; 7.6 Sampling distributions of order statistics; Problems; 7.7 Likelihood; Problems; 7.8 Sufficiency; Problems; 7.9 Minimal sufficiency; Problems; 7.10 Information in a sample; Problems; 7.11 Prior to posterior; Problems; 7.12 Principles of inference; 8. Estimation; 8.1 Mean squared error; Problems; 8.2 Efficiency; Problems; 8.3 Using sufficiency for variance reduction; Problems; 8.4 Consistency; 8.5 Method of moments; Problems |
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8.6 Maximum likelihood estimators8.7 Bayes estimates; Problems; 8.8 Interval estimates; Problems; 8.9 Estimating normal population parameters; Problems; 9. Testing Hypotheses; 9.1 Some generalities; 9.2 The likelihood ratio; Problems; 9.3 Tests: assessing evidence; Problems; 9.4 Tests: decision rules; Problems; 9.5 Bayesian testing; Problems; 9.6 Normal populations-the variance; Problems; 9.7 Normal populations-the mean; Problems; 9.8 Simple H0 vs. simple HA; Problems; 9.9 The Neyman-Pearson lemma; Problems; 9.10 The power function; 9.11 Power functions of t -- tests; Problems |
| Notes |
9.12 Uniformly most powerful tests |
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Print version record |
| Form |
Electronic book
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| ISBN |
9781351414173 |
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1351414178 |
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