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【原文書】 書名:Statistical Inference 2/E 作者:George Casella 出版社:CENGAGE ISBN:9780534243128 Table of contents 1. Probability Theory. Set Theory. Probability Theory. Conditional Probability and Independence. Random Variables. Distribution Functions. Density and Mass Functions. Exercises. Miscellanea. 2. Transformations and Expectations. Distribution of Functions of a Random Variable. Expected Values. Moments and Moment Generating Functions. Differentiating Under an Integral Sign. Exercises. Miscellanea. 3. Common Families of Distributions. Introductions. Discrete Distributions. Continuous Distributions. Exponential Families. Locations and Scale Families. Inequalities and Identities. Exercises. Miscellanea. 4. Multiple Random Variables. Joint and Marginal Distributions. Conditional Distributions and Independence. Bivariate Transformations. Hierarchical Models and Mixture Distributions. Covariance and Correlation. Multivariate Distributions. Inequalities. Exercises. Miscellanea. 5. Properties of a Random Sample. Basic Concepts of Random Samples. Sums of Random Variables from a Random Sample. Sampling for the Normal Distribution. Order Statistics. Convergence Concepts. Generating a Random Sample. Exercises. Miscellanea. 6. Principles of Data Reduction. Introduction. The Sufficiency Principle. The Likelihood Principle. The Equivariance Principle. Exercises. Miscellanea. 7. Point Estimation. Introduction. Methods of Finding Estimators. Methods of Evaluating Estimators. Exercises. Miscellanea. 8. Hypothesis Testing. Introduction. Methods of Finding Tests. Methods of Evaluating Test. Exercises. Miscellanea. 9. Interval Estimation. Introduction. Methods of Finding Interval Estimators. Methods of Evaluating Interval Estimators. Exercises. Miscellanea. 10. Asymptotic Evaluations. Point Estimation. Robustness. Hypothesis Testing. Interval Estimation. Exercises. Miscellanea. 11. Analysis of Variance and Regression. Introduction. One-way Analysis of Variance. Simple Linear Regression. Exercises. Miscellanea. 12. Regression Models. Introduction. Regression with Errors in Variables. Logistic Regression. Robust Regression. Exercises. Miscellanea. Appendix. Computer Algebra. References.
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【簡介】 Advances in computing technology, particularly in science and business, have increased the need for more statistical scientists to examine the huge amount of data being collected. Written by veteran statisticians, Probability and Statistical Inference, 10th Edition is an authoritative introduction to an in-demand field. It emphasizes the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variation. This applied overview of probability and statistics reinforces basic mathematical concepts with numerous real-world examples and applications to illustrate the relevance of key concepts. A good calculus background is needed, but no previous study of probability or statistics is required. It is designed for a 2-semester course, but also can be adapted for a 1-semester course. 【目錄】 Ch 1 Probability Ch 2 Discrete Distributions Ch 3 Continuous Distributions Ch 4 Bivariate Distributions Ch 5 Distributions of Functions of Random Variables Ch 6 Point Estimation Ch 7 Interval Estimation Ch 8 Tests of Statistical Hypotheses Ch 9 More Tests