Page 16 - Fundamentals of Probability and Statistics for Engineers

Preface

This book was written for an introductory one-semester or two-quarter course
in probability and statistics for students in engineering and applied sciences. No
previous knowledge of probability or statistics is presumed but a good under-
standing of calculus is a prerequisite for the material.
The development of this book was guided by a number of considerations
observed over many years of teaching courses in this subject area, including the
following:
. As an introductory course, a sound and rigorous treatment of the basic
principles is imperative for a proper understanding of the subject matter
and for confidence in applying these principles to practical problem solving.
A student, depending upon his or her major field of study, will no doubt
pursue advanced work in this area in one or more of the many possible
directions. How well is he or she prepared to do this strongly depends on
his or her mastery of the fundamentals.
. It is important that the student develop an early appreciation for applica-
tions. Demonstrations of the utility of this material in nonsuperficial applica-
tions not only sustain student interest but also provide the student with
stimulation to delve more deeply into the fundamentals.
. Most of the students in engineering and applied sciences can only devote one
semester or two quarters to a course of this nature in their programs.
Recognizing that the coverage is time limited, it is important that the material
be self-contained, representing a reasonably complete and applicable body of
knowledge.

The choice of the contents for this book is in line with the foregoing
observations. The major objective is to give a careful presentation of the
fundamentals in probability and statistics, the concept of probabilistic model-
ing, and the process of model selection, verification, and analysis. In this text,
definitions and theorems are carefully stated and topics rigorously treated
but care is taken not to become entangled in excessive mathematical details.

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