ISBN: 0-534-36888-3
2003
480 Pages. 7 3/8 x 9 1/4. 1-Color. Casebound.
Intended for the probability and random processes
course taught
in the Electrical Engineering or Electrical
and Computer
Engineering department. Taken at the junior/senior
level, all
electrical engineering students take this
course.
This book focuses on teaching probabilistic
and statistical
methods to upper-division electrical and
computer engineering (EECE)
students. It is the result of over 20 years
of teaching this
course in the rapidly changing environment
of EECE education. In
addition to being a readable and focused
book for EECE students,
the book is a teachable book for EECE instructors
with a variety
of technical backgrounds. The first part
of the book, Chapters 1-3,
contains fundamental probability material.
The second part,
Chapters 4-7, presents applications and extensions
based upon the
first three chapters. The four application
chapters may be
studied in any order, as they do not depend
on each other in any
essential way.
Features
Includes a wealth of applications for electrical
and computer
engineering (EECE) students.
Introduces functions with random features,
such as noise or
sinusoids with random phase, in Chapter 4.
The coverage is
restricted to "wide-sense stationary"
random processes,
a class of functions which are very useful
in modern practice and
also supply a starting point for more complicated
applications.
Illustrates the application of probability
to the reliability of
devices and software in Chapter 7. The chapter
focuses on failure
rates (hazard functions), a description that
engineers look to
for guidance in a variety of cases involving
system reliability.
Contains computer simulations written in
pseudocode as well as
applications in MATLABR. Computer exercises
appear at the end of
each chapter.
Features helpful appendices such as Appendix
A, a summary of
probability models discussed throughout the
book. Readers may
refer to Appendix A rather than leaf through
the various parts of
the book searching for features of a probability
model.
Table of Contents
1. PROBABILITY.
Why Probability? General Outline of this
Chapter. Probability
Calculations. Summary. Exercises. Computer
Exercises.
Bibliography.
2. SINGLE RANDOM VARIABLES.
Introduction. General Outline of this Chapter.
Probability Models.
Expectations. Characteristic Functions. Functions
of Single
Random Variables. Conditioned Random Variables.
Summary.
Exercises. Computer Exercises.
3. MULTIPLE RANDOM VARIABLES.
Introduction. General Outline of this Chapter.
Bivariate
Cumulative and Density Functions. Bivariate
Expectations.
Bivariate Transformations. Gaussian Bivariate
Random Variables.
Sums of Two Independent Random Variables.
Sums of IID Random
Variables. Conditional Joint Probabilities.
Selected Topics.
Summary. Exercises. Computer Exercises.
4. RANDOM PROCESSES.
Introduction. An Ensemble. Probability Density
Functions.
Independence. Expectations. Stationarity.
Correlation Functions.
Ergodic Random Processes. Power Spectral
Densities. Linear
Systems. Noise. Matched Filters. Least Mean-square
Filters.
Summary. Exercises. Computer Exercises.
5. STATISTICAL INFERENCES AND CONFIDENCE.
Introduction. The Maximum Likelihood Technique.
Estimation of
Mean and Variance. Summary. Exercises. Computer
Exercises.
6. RANDOM COUNTABLE EVENTS.
Introduction. Poisson Random Variables. Erlang
Random Variables.
Queuing. Summary. Exercises. Computer Exercises.
7. RELIABILITY.
Introduction. Reliability. Failure Rates.
System Reliability. The
Weibull Model. Accelerated Life Testing.
Summary. Exercises.
Computer Exercises.
APPENDICES.
Selected Probability Models. A Brief Review
of Counting
Techniques. A Uniform Random Number Generator.
Normalized
Gaussian Random Variables. Unit-Step and
Unit-Impulse Functions.
Statistics and Sample Data. A Central Limit
Theorem. Tables: Chi-Square
and Student's t. Wiener-Khinchin Relations.
ISBN: 0-534-39305-5
c 2004
Available May 2003
610 pp. 8 x 10 CB. 4-Color.
Intended for the one-term freshman/sophomore/junior
level
Introduction to Statistics course, offered
by just about every
college in the US and Canada, with an intermediate
or college
algebra prerequisite (no calculus is necessary).
Emphasizing the conceptual development of
statistical ideas, MIND
ON STATISTICS actively engages students and
explains topics in
the context of excellent examples and case
studies. This text
balances the spirit of statistical literacy
with statistical
methodology taught in the introductory statistics
course. Jessica
Utts and Robert Heckard built the book on
two learning premises:
(1) New material is much easier to learn
and remember if it is
related to something interesting or previously
known; (2) New
material is easier to learn if you actively
ask questions and
answer them for yourself. More than any other
text available,
MIND ON STATISTICS motivates students to
develop their
statistical intuition by focusing on analyzing
data and
interpreting results as opposed to focusing
on mathematical
formulation. The new edition of this exciting
text, enhanced with
new material and features, appeals to a wide
array of students
and instructors alike.
New to this Edition
New "Turn on Your Computer" features,
found throughout
the text, use Java applets from CyberGnostics'
CyberStats program.
These applets, which are on the CD-ROM accompanying
the text,
give students more opportunity for hands-on
learning and allow
students to explore statistics on their own.
Each chapter features new exercises, including
20 new basic
exercises per chapter that allow students
to practice and review.
These basic exercises complement the existing
and new conceptual
exercises found throughout each chapter.
Examples to enhance key concepts and calculations
have been added
throughout the text.
Coverage of random sampling and survey sampling
has been expanded.
A section has been added to the final chapter
discussing non-statistical
issues that can help citizens interpret statistical
studies
correctly.
New coverage of Nonparametric Statistics,
Analysis of Variance,
topics, and Ethics appear on the CD-ROM accompanying
the text.
BCA testing and homework makes grading and
testing extremely easy
for instructors. DuxStat, our online homework
feature, allows
students to complete all exercises in the
text and submit them
electronically for grading.
A stronger supplements package now includes
a Student Suite CD-ROM
featuring technology lab manuals for SPSS,
Minitab, Excel, and TI-83
graphing calculator, as well as applets from
CyberStats,
PowerPoint Presentation slides, data sets,
and much more. The
Student Suite CD-ROM is automatically packaged
with new texts at
no additional cost.
0-534-40689-0
693 pages Paper Bound 8 1/2 X 10 7/8
c 2004
INTRODUCTORY APPLIED BIOSTATISTICS provides
a solid and engaging
background for students learning to apply
and appropriately
interpret statistical applications in the
medical and public
health fields. The many examples drawn directly
from the authorsf
remarkable clinical experiences with applied
biostatistics makes
this text relevant, practical, and interesting
for students. This
flexible textbook encourages students to
master application
techniques by hand before moving on to computer
applications with
SAS programming code and output for each
technique covered in
every chapter. The majority of the textbook
addresses methods for
statistical inference, including one- and
two-sample tests for
means and proportions, analysis of variance
techniques,
correlation and regression analysis. For
each topic, the book
addresses methodology, including assumptions,
statistical
formulas, and appropriate interpretation
of results.
Features
Applications are introduced through real-world
examples that are
taken from the authors' own research in applied
biostatistics to
make them more relevant to the students'
area of study.
A flexible format allows students to master
techniques by hand as
well as using technology (SAS) to solve problems.
Each concept is
consequently introduced through a gby-handh
technique
followed by the corresponding SAS analysis.
Examples with relatively few subjects help
to illustrate
computations while minimizing the actual
computation
time?particularly important in mastering
gby-handh
computation. All of the techniques can be
applied to larger
problems in practice.
This highly regarded author team has been
teaching statistical
applications for over 50 years, and all three
are highly
experienced researchers.
"Key Formulas" appear at the end
of each chapter, and
include the application, the notation, and
a description of the
formulas that are applicable to the concepts
introduced in that
chapter.
"Statistical Computing" sections,
also at the end of
each chapter, introduce the SAS procedures
and applications that
apply to each newly introduced concepts.
0-534-39951-7
510 pages Case Bound 7 3/8 x 9 1/4
c 2004 Available Now
David Howell's practical approach focuses
on the context of
statistics in behavioral research, with an
emphasis on looking at
data before jumping into a test. This provides
students with an
understanding of the logic behind the statistics:
why and how
certain methods are used rather than just
doing techniques by
rote. Students move beyond number crunching
to discover the
meaning of statistical results and how they
relate to the
research questions being asked. FUNDAMENTAL
STATISTICS FOR THE
BEHAVIORAL SCIENCES contains an abundance
of real data and
research studies as a base and moves through
an analysis of data.
New to the Edition
New Java applets, which are adapted from
Gary McClelland's SEEING
STATISTICS, appear in nearly every chapter.
These applets allow
students to visualize statistical concepts
using Java technology.
In keeping with the recommendations of the
American Psychological
Association, the text places a greater emphasis
on effect sizes
in experimental reports.
The Student Suite CD-ROM includes the Student
Handbook at no
additional charge. This valuable CD-ROM offers
students access to
hints and tips, as well as complete solutions
to selected
exercises from the text. It also contains
Data Sets formatted for
SPSS, Minitab, JMP, Excel, and ASCII, and
selected Java applets
from SEEING STATISTICS.
An SPSS manual specific to the text is now
available for students.
The greatly enhanced Instructor Suite CD-ROM
support includes
Microsoft PowerPoint slides, test items,
complete solutions, as
well as all the components of the Student
Suite.
BCA is our electronic testing and course
management program,
available both online and on CD-ROM. With
no need for plug-ins or
downloads, BCA offers algorithmically-generated
problem values
and machine-graded free response mathematics
0-534-40806-0
726 pages Hardcover 8 x 10
c 2004 Available Now
A FIRST COURSE IN STATISTICAL METHODS addresses
a pressing need
in the methods course?a shorter text designed
for a one-term
course. By selecting and revising material
from their best-selling
two-semester text, AN INTRODUCTION TO STATISTICAL
METHODS AND
DATA ANALYSIS, Fifth Edition, the authors
created an ideal book
for a one-term course in statistical methods.
Based on the belief
that statistics is a thought process tied
to the scientific
method, the text utilizes a 5-step approach:
1) defining the
problem, 2) collecting data, 3) summarizing
data, 4) analyzing
and interpreting the data, and 5) communicating
the results of
the analysis.
Features
In order to encourage students with limited
mathematical
background and ability, the authors have
taken great care to
ensure that the material presented uses understandable,
non-technical
descriptions of concepts, without relying
solely on formulas.
gEncounters with Real Datah sections appear
at the end of
appropriate chapters. These sections make
use of real data sets
compiled by Bruce Trumbo, and taken from
his casebook, LEARNING
STATISTICS WITH REAL DATA. These real data
sets present relevant,
interesting challenges to students, requiring
multiple methods
for data analysis.
Examples and exercises are taken from various
disciplines,
appealing to a wide range of students. In
addition, the examples
and exercises, many of which have been taken
from journal
articles, newspapers, or the authorsf own
consulting
experiences, have been praised for their
practicality and
usefulness.
The book makes wide use of graphical displays
of data that help
students understand data and evaluate critical
assumptions.
The authorsf approach emphasizes interpretation
and analysis of
data over computation.
The technology friendly approach allows computers
to handle
formulas so that students can focus on interpretation
and
analysis of data. Computer output from popular
statistical data
analysis packages, including Minitab, SAS,
JMP, SPSS, and Stata,
appears in the examples and exercises.