{"product_id":"models-for-probability-and-statistical-inference-theory-and-applications-9780470073728","title":"Models for Probability and Statistical Inference   Theory and Applications","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eServing as a text for a two semester sequence on probability and statistical inference complex Models for Probability and Statistical Inference: Theory and Applications features exercises throughout the book and selected answers (not solutions). Each section is followed by a selection of problems, from simple to more complex.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\"The prose throughout the book is clear and well aimed at first-year master's student who is intelligent but not yet statistically sophisticated. Examples are clear and well chosen.\" (\u003ci\u003eBiometrics\u003c\/i\u003e, March 2009)  \u003cp\u003e\"Highly recommended. Graduate students through professionals.\" (\u003ci\u003eCHOICE\u003c\/i\u003e, May 2008)\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cb\u003e1. Probability Models.\u003c\/b\u003e  \u003cp\u003e1.1 Discrete Probability Models.\u003c\/p\u003e \u003cp\u003e1.2 Conditional Probability and Independence.\u003c\/p\u003e \u003cp\u003e1.3 Random Variables.\u003c\/p\u003e \u003cp\u003e1.4 Expectation.\u003c\/p\u003e \u003cp\u003e1.5 The Variance.\u003c\/p\u003e \u003cp\u003e1.6 Covariance and Correlation.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2. Special Discrete Distributions.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 The Binomial Distribution.\u003c\/p\u003e \u003cp\u003e2.2 The Hypergeometric Distribution.\u003c\/p\u003e \u003cp\u003e2.3 The Geometric and Negative Binomial Distributions.\u003c\/p\u003e \u003cp\u003e2.4 The Poisson Distribution.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3. Continuous Random Variables.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Continuous RV's and Their Distributions.\u003c\/p\u003e \u003cp\u003e4.2 Expected Values and Variances.\u003c\/p\u003e \u003cp\u003e4.3 Transformations of Random Variables.\u003c\/p\u003e \u003cp\u003e4.4Joint Densities.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Special Continuous Distributions.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 The Normal Distribution.\u003c\/p\u003e \u003cp\u003e4.2 The Gamma Distribution.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5. Conditional Distributions.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 The Discrete Case.\u003c\/p\u003e \u003cp\u003e5.2 Conditional Expectations for the Discrete Case.\u003c\/p\u003e \u003cp\u003e5.3 Conditional Densities and Expectations for Continuous RV's.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6. Limit Laws.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Moment Generating Functions.\u003c\/p\u003e \u003cp\u003e6.2 Convergence in Probability and in Distribution.\u003c\/p\u003e \u003cp\u003e6.3 The Central Limit Theorem.\u003c\/p\u003e \u003cp\u003e6.4 The Delta-Method.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7. Estimation.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Point Estimation.\u003c\/p\u003e \u003cp\u003e7.2 The Method of Moments.\u003c\/p\u003e \u003cp\u003e7.3 Maximum Likelihood.\u003c\/p\u003e \u003cp\u003e7.4 Consistency.\u003c\/p\u003e \u003cp\u003e7.5 The Ω-Method.\u003c\/p\u003e \u003cp\u003e7.6 Confidence Intervals.\u003c\/p\u003e \u003cp\u003e7.7 Fisher Information, The Cramer-Rao Bound, and Asymptotic Normality of MLE's.\u003c\/p\u003e \u003cp\u003e7.8 Sufficiency.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8. Testing Hypotheses.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction.\u003c\/p\u003e \u003cp\u003e8.2 The Neyman-Pearson Lemma.\u003c\/p\u003e \u003cp\u003e8.3 The Likelihood Ratio Test.\u003c\/p\u003e \u003cp\u003e8.4 The p-Value and the Relationship Between Tests of Hypotheses and Confidence Intervals.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9. The Multivariate Normal, Chi-square, t, and F-Distributions.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 The Multivariate Normal Distribution.\u003c\/p\u003e \u003cp\u003e9.2 The Central and Noncentral Chi-Square Distributions.\u003c\/p\u003e \u003cp\u003e9.3 Student's t-Distribution.\u003c\/p\u003e \u003cp\u003e9.4 The F-Distribution.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10.3 Nonparametric Statistics.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 The Wilcoxon Test and Estimator.\u003c\/p\u003e \u003cp\u003e10.2 One Sample Methods.\u003c\/p\u003e \u003cp\u003e10.3 The Kolmogorov-Smirnov Tests.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11. Linear Models.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 The Principle of Least Squares.\u003c\/p\u003e \u003cp\u003e11.2 Linear Models.\u003c\/p\u003e \u003cp\u003e11.3 F-Tests for H0.\u003c\/p\u003e \u003cp\u003e11.4 Two-Way Analysis of Variance..\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12. Frequency Data.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Logistic Regression.\u003c\/p\u003e \u003cp\u003e12.2 Two-Way Frequency Tables.\u003c\/p\u003e \u003cp\u003e12.3 Chi-Square Goodness of Fit Tests.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13. Miscellaneous Topics.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Survival Analysis.\u003c\/p\u003e \u003cp\u003e13.2 Bootstrapping.\u003c\/p\u003e \u003cp\u003e13.3 Bayesian Statistics.\u003c\/p\u003e \u003cp\u003e13.4 Sampling.\u003c\/p\u003e","brand":"Wiley-Blackwell","offers":[{"title":"Default Title","offer_id":53515413750103,"sku":"9780470073728","price":129.56,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/models-for-probability-and-statistical-inference-theory-and-applications-9780470073728","provider":"Book Curl","version":"1.0","type":"link"}