All of Statistics: A Concise Course in Statistical Inference-with 95 Figures

By: Wasserman,LarryMaterial type: TextTextSeries: Springer texts in statisticsPublication details: New York : Springer, ©2004Description: xix, 442 pages : illustrationsISBN: 9780387402727; 0387402721 Subject(s): Mathematical statisticsDDC classification: 519.5
Contents:
I. Probability -- 1. Probability -- 2. Random Variables -- 3. Expectation -- 4. Inequalities -- 5. Convergence of Random Variables -- II. Statistical Inference -- 6. Models, Statistical Inference and Learning -- 7. Estimating the CDF and Statistical Functionals -- 8. The Bootstrap -- 9. Parametric Inference -- 10. Hypothesis Testing and p-values -- 11. Bayesian Inference -- 12. Statistical Decision Theory -- III. Statistical Models and Methods -- 13. Linear and Logistic Regression -- 14. Multivariate Models -- 15. Inference About Independence -- 16. Causal Inference -- 17. Directed Graphs and Conditional Independence -- 18. Undirected Graphs -- 19. Log-Linear Models -- 20. Nonparametric Curve Estimation -- 21. Smoothing Using Orthogonal Functions -- 22. Classification -- 23. Probability Redux: Stochastic Processes -- 24. Simulation Methods.
Summary: "This book is for people who want to learn probability and statistics quickly. It brings together many of the main ideas in modern statistics in one place. The book is suitable for students and researchers in statistics, computer science, data mining, and machine learning." "This book covers a much wider range of topics than a typical introductory text on mathematical statistics. It includes modern topics like nonparametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is assumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. The text can be used at the advanced undergraduate and graduate levels."--Jacket.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
Reference Books Reference Books Main Library
Reference 		Reference 519.5 WAS (Browse shelf(Opens below)) Available 012094
Reference Books Reference Books Main Library
Reference 		Reference 519.5 WAS (Browse shelf(Opens below)) Available 011304
Total holds: 0

Bibliography & index

I. Probability --
1. Probability --
2. Random Variables --
3. Expectation --
4. Inequalities --
5. Convergence of Random Variables --
II. Statistical Inference --
6. Models, Statistical Inference and Learning --
7. Estimating the CDF and Statistical Functionals --
8. The Bootstrap --
9. Parametric Inference --
10. Hypothesis Testing and p-values --
11. Bayesian Inference --
12. Statistical Decision Theory --
III. Statistical Models and Methods --
13. Linear and Logistic Regression --
14. Multivariate Models --
15. Inference About Independence --
16. Causal Inference --
17. Directed Graphs and Conditional Independence --
18. Undirected Graphs --
19. Log-Linear Models --
20. Nonparametric Curve Estimation --
21. Smoothing Using Orthogonal Functions --
22. Classification --
23. Probability Redux: Stochastic Processes --
24. Simulation Methods.


"This book is for people who want to learn probability and statistics quickly. It brings together many of the main ideas in modern statistics in one place. The book is suitable for students and researchers in statistics, computer science, data mining, and machine learning." "This book covers a much wider range of topics than a typical introductory text on mathematical statistics. It includes modern topics like nonparametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is assumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. The text can be used at the advanced undergraduate and graduate levels."--Jacket.

There are no comments on this title.

to post a comment.

© University of Vavuniya

---