Introduction to Mathematical Statistics and Its Applications, An, 6th edition

For courses in Mathematical Statistics.

The principles of statistics and data modeling

An Introduction to Mathematical Statistics and Its Applications, 6th Edition is a high-level calculus student's first exposure to mathematical statistics. It provides students who have already taken 3 or more semesters of calculus with the background to apply statistical principles. Meaty enough to guide a 2-semester course, it touches on both statistics and experimental design, which teaches students various ways to analyze data. It gives computational-minded students a necessary and realistic exposure to identifying data models.

Hallmark features of this title

• Standard statistical techniques are presented in a mathematical context, letting students grasp the hypotheses behind each application.
• Thoroughly dives into introductory topics such as the theoretical aspects of mathematical statistics and the development of the statistical theory.
• Appropriately covers technical topics in a way that is accessible to graduate-level students in their first course in mathematical statistics or for professionals an outside techniques book.
• Presents mathematical statistics as a subject students can encounter in the real world, with vivid case studies and applicable examples.
• Integrated review of calculus weaves in a topic students are familiar with while reinforcing related principles.
• At-home exercises help students practice the application of principles taught in class.

New and updated features of this title

• A new downloadable chapter on variance analysis as it applies to factorial data: Touches crucial topics such as 2-factor factorials, 3-factor factorials, 2n designs, and fractional factorials, at a high level.
• 18 new Case Studies appear throughout the edition.
• Content changes:
  • Chapter 2 contains 10 new examples, including a repeated-independent-trials analysis of the often-quoted “Caesar's last breath” problem. In Chapter 4, an Appendix has been added which summarizes important properties of the most frequently used pdfs.
  • Chapter 5, section 5.2 on parameter estimation has been rewritten; the margin of error portion of Section 5.3 has been completely redone. Chapter 7 includes 7 new Case Studies. Chapter 8 has expanded discussions of the different data models, with a completely new model on factorial data.
  • In Chapter 11, section on nonlinear models has been revised to emphasize their relationship to different laws of growth. Chapter 12 contains a sections that explains how the entire ANOVA table for a set of k-sample data can be “reconstructed” without knowing any of the individual measurements.