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 theFifth 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.
Features
- Standard statistical techniques are presented in a mathematical context, enabling students to see the underlying hypotheses for
the applications.
- Superior treatment of real-world data uses case studies and practical, worked-out examples to motivate statistical reasoning and
demonstrate the application of statistical methods to a wide variety of real-world situations.
- Numerous and interesting homework exercises engage the student and illuminate the main points of the text.
- The authors' writing style presents concepts and applications in an engaging narrative.
- Sound coverage of the theoretical aspects of mathematical statistics carefully explains the mathematics and development of the
statistical theory.
- Accessible mathematical prerequisites mediate between a techniques book and a graduate-level first course in mathematical
statistics.
- Integrated review of calculus reinforces students' prior knowledge by reviewing calculus as necessary throughout the presentation.
New to this Edition
- “About the Data” notes now follow case studies in order to encourage students to think critically about a data set's assumptions,
interpretations, and implications.
- Substantial rewriting of the Data Models chapter (Chapter 8) makes its main points more accessible.
- Many examples and case studies have been updated, while some have been deleted, and others added.
- Extensively rewritten and revised content includes Section 3.8 “Transforming and Combining Random Variables,” and Section
3.9, “Further Properties of the Mean and Variance.” Section 3.9 now includes a discussion of covariances so that sums of random
variables can be dealt with in more generality.
- Chapter 5, “Estimation,” now includes an introduction to bootstrapping.
- New material on the noncentral t distribution and its role in calculating Type II error probabilities is provided in Chapter
7, “Inferences Based on the Normal Distribution.”
- Chapter 9, “Two-Sample Inferences,” now includes a derivation of Welch's approximation for testing the differences of two means
in the case of unequal variances.
1. Introduction
2. Probability
3. Random Variables
4. Special Distributions
5. Estimation
6. Hypothesis Testing
7. Inferences Based on the Normal Distribution
8. Types of Data: A Brief Overview
9. Two-Sample Inferences
10. Goodness-of-Fit Tests
, etc.