Description 
1 online resource 
Series 
Springer texts in statistics

Contents 
Probability  Random Variables  Expectation  Inequalities  Convergence of Random Variables  Models, Statistical Inference and Learning  Estimating the CDF and Statistical Functionals  The Bootstrap  Parametric Inference  Hypothesis Testing and pvalues  Bayesian Inference  Statistical Decision Theory  Linear and Logistic Regression  Multivariate Models  Inference about Independence  Causal Inference  Directed Graphs and Conditional Independence  Undirected Graphs  Loglinear Models  Nonparametric Curve Estimation  Smoothing Using Orthogonal Functions  Classification  Probability Redux: Stochastic Processes  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 followup 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 level. Larry Wasserman is Professor of Statistics at Carnegie Mellon University. He is also a member of the Center for Automated Learning and Discovery in the School of Computer Science. His research areas include nonparametric inference, asymptotic theory, causality, and applications to astrophysics, bioinformatics, and genetics. He is the 1999 winner of the Committee of Presidents of Statistical Societies Presidents' Award and the 2002 winner of the Centre de recherches mathematiques de MontrealStatistical Society of Canada Prize in Statistics. He is Associate Editor of The Journal of the American Statistical Association and The Annals of Statistics. He is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics 
Bibliography 
Includes bibliographical references (pages 423430) and index 
Notes 
English 

Print version record 
Subject 
Mathematical statistics


Statistics as Topic

Form 
Electronic book

LC no. 
2003062209 
ISBN 
6610189668 

9786610189663 

1280189665 

9781280189661 

9780387217369 
