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Mathematical Statistics with Applications 7th Edition + Solution Manual



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Author: Dennis Wackerly and William Mendenhall

Publisher: Thomson Brooks

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Publish Date: 2008

ISBN-10: 495110817

Pages: 944

File Type: PDF

Language: English

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Book Preface

The Purpose and Prerequisites of this Book

Mathematical Statistics with Applications was written for use with an undergraduate 1-year sequence of courses (9 quarter- or 6 semester-hours) on mathematical statistics. The intent of the text is to present a solid undergraduate foundation in statistical theory while providing an indication of the relevance and importance of the theory in solving practical problems in the real world. We think a course of this type is suitable for most undergraduate disciplines, including mathematics, where contact with applications may provide a refreshing and motivating experience. The only mathematical prerequisite is a thorough knowledge of first-year college calculus— including sums of infinite series, differentiation, and single and double integration.

Our Approach

Talking with students taking or having completed a beginning course in mathematical statistics reveals a major flaw in many courses. Students can take the course and leave it without a clear understanding of the nature of statistics. Many see the theory as a collection of topics, weakly or strongly related, but fail to see that statistics is a theory of information with inference as its goal. Further, they may leave the course without an understanding of the important role played by statistics in scientific investigations. These considerations led us to develop a text that differs from others in three ways:

• First, the presentation of probability is preceded by a clear statement of the objective of statistics—statistical inference—and its role in scientific research. As students proceed through the theory of probability (Chapters 2 through 7), they are reminded frequently of the role that major topics play in statistical inference. The cumulative effect is that statistical inference is the dominating theme of the course.

• The second feature of the text is connectivity. We explain not only how major topics play a role in statistical inference, but also how the topics are related to one another. These integrating discussions appear most frequently in chapter introductions and conclusions.

• Finally, the text is unique in its practical emphasis, both in exercises throughout the text and in the useful statistical methodological topics contained in Chapters 11–15, whose goal is to reinforce the elementary but sound theoretical foundation developed in the initial chapters.

The book can be used in a variety of ways and adapted to the tastes of students and instructors. The difficulty of the material can be increased or decreased by controlling the assignment of exercises, by eliminating some topics, and by varying the amount of time devoted to each topic. A stronger applied flavor can be added by the elimination of some topics—for example, some sections of Chapters 6 and 7—and by devoting more time to the applied chapters at the end.


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