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Probability and Statistical Inference
Hogg, Robert V.; Tanis, Elliot A.
Written by two leading statisticians, this applied introduction to the mathematics of probability and statistics emphasizes the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variation. Designed for students with a background in calculus, this book continues to reinforce basic mathematical concepts with numerous real-world examples and applications to illustrate the relevance of key concepts.

Introduction to probability Theory and Statistical
Larson, Harold J.
Discusses probability theory and to many methods used in problems of statistical inference. The Third Edition features material on descriptive statistics. Cramer-Rao bounds for variance of estimators, two-sample inference procedures, bivariate normal probability law, F-Distribution, and the analysis of variance and non-parametric procedures. Contains numerous practical examples and exercises.

Introduction to Mathematical Statistics
Hogg, Robert V.; McKean, Joseph W.; Craig, Allen T.
This classic book retains its outstanding ongoing features and continues to provide readers with excellent background material necessary for a successful understanding of mathematical statistics. Chapter topics cover classical statistical inference procedures in estimation and testing, and an in-depth treatment of sufficiency and testing theory—including uniformly most powerful tests and likelihood ratios. Many illustrative examples and exercises enhance the presentation of material throughout the book. For a more complete understanding of mathematical statistics.

An Introduction to Mathematical Statistics
Larsen, Richard J.; Marx, Morris L.
Noted for its integration of real-world data and case studies, this text offers sound coverage of the theoretical aspects of mathematical statistics. The authors demonstrate how and when to use statistical methods, while reinforcing the calculus that students have mastered in previous courses. Throughout the Fifth Edition, the authors have added and updated examples and case studies, while also refining existing features that show a clear path from theory to practice.CourseSmart textbooks do not include any media or print supplements that come packaged with the bound book.

Mathematical Statistics
Bickel, Peter J.; Doksum, Kjell A.
A classic, time-honored introduction to the theory and practice of statistics modeling and inference revised to reflect the changing focus of Statistics and the mathematics background of today's students. Coverage begins with the more general nonparametric point of view and then looks at parametric models as submodels of the nonparametric ones which can be described smoothly by Euclidean parameters. Although some computational issues are discussed, this is very much a book on theory. A second volume treating more advanced topics is in preparation.