All of statistics : a concise course in statistical inference
Wasserman, Larry
All of statistics : a concise course in statistical inference / Larry Wasserman - New York : Springer, ©2004 - xix, 442p : illustrations ; 24 cm
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
9781441923226
International Book Distributors :Flat No 17, Prakash Apartment 4405/2, 5 Ansari Road Darya Ganj New Delhi
Mathematics
Probabilities and applied mathematics
Statistics.
Mathematical statistics.
Statistics as Topic
519.5 WAS
All of statistics : a concise course in statistical inference / Larry Wasserman - New York : Springer, ©2004 - xix, 442p : illustrations ; 24 cm
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
9781441923226
International Book Distributors :Flat No 17, Prakash Apartment 4405/2, 5 Ansari Road Darya Ganj New Delhi
Mathematics
Probabilities and applied mathematics
Statistics.
Mathematical statistics.
Statistics as Topic
519.5 WAS
