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 Probability and Statistical Inference, 2nd  ������   ������ : Bartoszynski & Niewiadomska-Bugaj ���ǻ� : Wiley �Ǽ� : 2 edition �������� : 647 ISBN : 9780471696933 ��������� : �Ա�Ȯ���� 2�� �̳� �ֹ����� : �� �������� : 42,000�� ( ������ ) ������ : 1,260 Point     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 outstanding new edition continues to encouragereaders to recognize and fully understand the why, not just the how, behind the concepts,theorems, and methods of statistics. Clear explanations are presented and appliedto various examples that help to impart a deeper understanding of theorems and methods�from fundamental statistical concepts to computational details. Additional features of this Second Edition include: A new chapter on random samples Coverage of computer-intensive techniques in statistical inference featuring Monte Carlo and resampling methods, such as bootstrap and permutation tests, bootstrap confidence intervals with supporting R codes, and additional examples available via the book's FTP site Treatment of survival and hazard function, methods of obtaining estimators, and Bayes estimating Real-world examples that illuminate presented concepts Exercises at the end of each section Providing a straightforward, contemporary approach to modern-day statistical applications, Probability and Statistical Inference, Second Edition is an ideal text for advanced undergraduate- and graduate-level courses in probability and statistical inference. It also serves as a valuable reference for practitioners in any discipline who wish to gain further insight into the latest statistical tools. Preface. 1. Experiments, Sample Spaces, and Events. 2. Probability. 3. Counting. 4. Conditional Probability; Independence. 5. Markov Chains*. 6. Random Variables: Univariate Case. 7. Random Variables: Multivariate Case. 8. Expectation. 9. Selected Families of Distributions. 10. Random Samples. 11. Introduction to Statistical Inference. 12. Estimation. 13. Testing Statistical Hypotheses. 14. Linear Models. 15. Rank Methods. 16. Analysis of Categorical Data. Statistical Tables. Bibliography. Answers to Odd-Numbered Problems. Index. "I found this book quite thorough and very well written. I liked it a lot because, although not advanced, it does not lack mathematical rigour. I thouroughly recommended for anybody who needs a sound basis for probability and statistics."   Introduction to Partial Di... -Zachmanoglou- (Dover)  Real Analysis Modern Techn... -Folland- (Wiley)  A First Course in Abstract... -John B. Fraleigh- (Addison-Wesley)   �ٽɹ̺������� 9�� 12.... �ֹ� ��� ��û�մϴ�. ��û�帳�ϴ�.       Applied Statistics... Introductory Stati... Elementary Statist... Introductory Stati... Introduction to Ma...   