**Edited by Connie M. Borror**

Applied Statistics: A First Course in Inference.

by Franklin A. Graybill, Hariharan
K. Iyer, and Richard K. Burdick

Applied Statistics for Engineers and Scientists

by Joseph D. Petruccelli, Balgobin
Nandram and Minghui Chen

An Introduction to Statistical Methods and Data
Analysis, 5th ed.

by R. Lyman Ott and Michael Longnecker

Probability and Statistics for Engineering and
the Sciences, 5th ed.

by Jay L. Devore

*The following brief editor's reviews are of new editions,
collections of papers, or other books that may be of interest
to some readers. *

*Connie M. Borror*, Industrial and Management Sys-tems
Engineering, Arizona State University, Tempe, AZ 85287-5906.

**Applied Statistics:
A First Course in Inference** by *Franklin A. Graybill,
Hariharan K. Iyer, and Richard K. Burdick*. Prentice Hall,
Inc., Upper Saddle River, NJ, 1998. xvii + 461. $80.00

THE targeted audience of Applied Statistics: A First Course in Inference consists of undergraduate students who have taken college-level algebra and have no previous exposure to statistics. The text is appropriate for an introductory course for students in disciplines such as the social sciences and business, but not necessarily for students in the engineering sciences, where more emphasis on probability concepts may be needed.

The chapter titles are:

Chapter 1. Data and Statistical Methods

Chapter 2. Populations, Variables, Parameters, and Samples

Chapter 3. Con dence Intervals for a Population Proportion

Chapter 4. Processing Data

Chapter 5. Median and Interquartile Range : Mean and Standard Deviation

Chapter 6. The Normal Population

Chapter 7. Inference for a Population Mean and Median for any Population

Chapter 8. Statistical Tests

Chapter 9. Simple Linear Regression

Interlude: Critical Assessment of Statistical Studies

Chapter 10. Comparing Population Proportions: Contingency Tables

Chapter 11. Comparing Population Means

Chapter 12. Multiple Regression

Chapter 13. Process Improvement

Chapter 14. Sample Surveys.

There are self-test problems given throughout the text with complete solutions at the end of each chapter. A summary of the key concepts and terms and numerous exercises are also provided. For a one-semester course, Chapters 1 through 9 could be cov-ered in detail along with sections of interest in Chapters 10 through 14.

The chapter titled "Interlude" provides interesting and practical guidelines on applying the basic techniques provided in the previous nine chapters. The stated goal of this chapter is to provide practical guidelines to help you better understand and interpret the results of a statistical study. The subsections of this chapter are entitled:

I.1 Introduction

I.2 Evaluating Statistical and Judgment Inferences

I.3 Understanding Cause-and-Effect Relationships.

The Interlude is an excellent addition to the text. The authors have successfully used this chapter as a transition from the basic techniques in Chapters 1 through 9 to the more advanced techniques presented in Chapters 10 through 14.

Computer output from Minitab and Excel is used sparingly throughout the text. Supplemental mate-rial available for use with the text includes an instructor s solution manual, a test bank, and a data disk (provided with the text). The authors have also developed an Excel Companion (available from the publisher) , which teaches the student how to use Excel to perform many of the analyses presented.

Overall, the text is a well-written, comprehensive introduction to basic statistics. Students with little or no prior experience in statistics will nd this text easy to read and use. Applied Statistics should be seriously considered for an introductory course aimed at students outside engineering and statistics departments.

**Applied Statistics
for Engineers and Scientists** by *Joseph D. Petruccelli,
Balgobin Nandram, and Minghui Chen.* Prentice Hall, Inc.,
Upper Saddle River, NJ 07458. 1999, xvi + 943 pp., $101.00.

AS the title indicates, Applied Statistics for Engineers and Scientists is designed for engineering and science undergraduate students with one semester of di erential and integral calculus. This textbook resulted from the authors teaching experiences at Worcester Polytechnic Institute. Over the years, an introductory statistics course was updated to emphasize computer intensive statistical techniques and active and interactive learning. The organization of the material in this textbook is a direct result of the changes and enhancements to the course. The chapter titles are:

Chapter 1. Introduction to Data Analysis

Chapter 2. Summarizing Data

Chapter 3. Designing Studies and Obtaining Data

Chapter 4. An Introduction to Statistical Modeling

Chapter 5. Introduction to Inference: Estimation and Prediction

Chapter 6. Hypothesis Tests

Chapter 7. The Relationship Between Two Variables

Chapter 8. Multiple Regression

Chapter 9. The One-Way Model

Chapter 10. The Factorial Model

Chapter 11. Distribution-Free Inference

Chapter 12. 2^{k}Designs

Chapter 13. 2^{k-p}Designs and Their Role in Quality Improvement

Chapter 14. Response-Surface Methodology

Chapter 15. Statistical Process Control.

The book can be used in either a one or two semester course. There are several components of this book which set it apart from competing text-books. Aside from numerous exercises of varying diffculty, each chapter contains Miniprojects, which can be accomplished by small teams of students, and Labs. The Labs are well structured, with detailed instructions for the students. The types of Labs provided are called Hands-on, Computer Simulation, and Computer Data Analysis. Hands-on Labs are designed so that students produce data through a particular activity. The Miniprojects and Labs provide for the application of material covered in each chapter by students. The authors have also included capstone projects at various locations throughout the text. The capstone projects are designed to be completed over one-half of a semester or a whole semester.

A companion website for the textbook is located at www.prenhall.com petruccelli and provides a wealth of information and supporting materials. Datasets are provided in three formats: Minitab projects, SAS, and text. There are links to educational, economic, health, and sports databases. Links to several associations and journals are also provided. Unfortunately, several of the links to databases were invalid.

In spite of the outdated links at
the companion website, *Applied Statistics for Engineers
and Scientists *is a well-organized text that successfully
integrates basic methods and techniques with computer software
and active data collection by students. This bookwould be
an excellent choice for a course that consists of both a lecture
and a lab section (where students are in smaller groups for
data collection and analysis activities).

**An Introduction to
Statistical Methods and Data Analysis, 5th ed.** by
*R. Lyman Ott and Michael Longnecker*. Duxbury, Paci
c Grove, CA, 2001. xvii + 1152. $96.95.

THE fifth edition of An Introduction to Statistical Methods and Data Analysis maintains the organization and depth of material coverage found in the previous editions, with several enhancements and additions. As with the previous four editions, the intended audience consists of advanced undergraduate or graduate students with "... a minimal mathematical background (high school algebra) and no prior coursework in statistics". The textbook would be most appropriate for disciplines such as the social sciences and education.

The topics have been separated into seven parts with a total of twenty chapters. The parts and chapters are:

**Part 1. Introduction**

Chapter 1. What is Statistics?

**Part 2. Collecting Data **

Chapter 2. Using Surveys and Scientific Studies to Gather Data

**Part 3. Summarizing Data **

Chapter 3. Data Description

**Part 4. Tools and Concepts **

Chapter 4. Probability and Probability Distributions

**Part 5. Analyzing Data: Central Values, Variances and
Proportions **

Chapter 5. Inferences about Population Central Values

Chapter 6. Inferences Comparing Two Population Central Values

Chapter 7. Inferences about Population Variances

Chapter 8. Inferences about More than Two Population Central Values

Chapter 9. Multiple Comparisons

Chapter 10. Categorical Data

**Part 6. Analyzing Data: Regression Methods and Model Building
**

Chapter 11. Linear Regression and Correlation

Chapter 12. Multiple Regression and the General Linear Model

Chapter 13. More on Multiple Regression

**Part 7. Design of Experiments and Analysis of Variance
**

Chapter 14. Design Concepts for Experiments and Studies

Chapter 15. Analysis of Variance for Standard Designs

Chapter 16. The Analysis of Covariance

Chapter 17. Analysis of Variance for Some Fixed-, Random-, and Mixed-Effects Models

Chapter 18. Repeated Measures and Crossover Designs

Chapter 19. Analysis of Variance for Some Unbalanced Designs

Chapter 20. Communicating and Documenting the Results of Analyses.

Previous editions of this text have been used successfully in service courses in which only portions of the material covered in the book are necessary. For example, portions of Part 5 and all of Part 7 provide sufficient material for a service course in the study of the analysis of variance for students with previous exposure to basic statistics.

Several new features have been included in the fifth edition. New case studies are provided in almost all chapters and the exercises and examples have been updated and expanded to cover numerous disciplines. A new chapter has been added outlining the importance of designing experiments and studies prior to collecting data in order to carefully consider all important factors. More computer resources and output are provided than in previous versions, without relying too heavily on a particular statistical package. Some of the statistical packages utilized include SAS, Minitab, Systat, JMP, STATA, and SPSS.

In the Preface, the authors state that the data sets, errata, answers to selected exercises, and additional resources can be accessed through the Duxbury website by selecting Online Book Companions. At the time this review was written, there was no link for this textbook. Therefore, answers to selected exercises and any errata that may exist could not be found. The data sets could not be reached through the link Online Book Companions, but were available at www.duxbury.com/datasets.htm.

Each topic of discussion is addressed, generally, in the following manner: 1) de nitions are provided for the statistical procedure; (2) the appropriate formulas (calculations) are presented; (3) the application of statistical software for implementing the procedure is demonstrated; and 4) the interpretation and validity of results is discussed. Overall, the text is well written, has an emphasis on interpretation rather than computation, and would be an appropriate textbook for an introductory statistics class or as a reference text.

**Probability and Statistics
for Engineering and the Sciences, 5th ed.** by *Jay
L. Devore*. Duxbury, Paci c Grove, CA, 2000. xvi + 775
pp. $94.95.

NOW in its fth edition, Probability and Statistics for Engineering and the Sciences continues to be one of the most popular and widely used textbooks on the market today. Engineering and the sciences are the targeted disciplines, but those in the social sciences and business may nd this text useful as well. The text can be used for a one or two semester undergraduate statistics course. The students should have had at least one semester or two quarters of differential and integral calculus, although calculus is emphasized only in Chapter 4 and portions of Chapters 5 and 6.

There are sixteen chapters:

Chapter 1. Overview and Descriptive Statistics

Chapter 2. Probability

Chapter 3. Discrete Random Variables and Probability Distributions

Chapter 4. Continuous Random Variables and Probability Distributions

Chapter 5. Joint Probability Distributions and Random Samples

Chapter 6. Point Estimation

Chapter 7. Statistical Intervals Based on a Single Sample

Chapter 8. Tests of Hypotheses Based on a Single Sample

Chapter 9. Inferences Based on Two Samples

Chapter 10. The Analysis of Variance

Chapter 11. Multifactor Analysis of Variance

Chapter 12. Simple Linear Regression and Correlation

Chapter 13. Nonlinear and Multiple Regression

Chapter 14. The Analysis of Categorical Data

Chapter 15. Distribution-Free Procedures

Chapter 16. Quality Control Methods.

Several changes to the 4th edition are apparent in the text. The sampling distribution material found in Chapter 5 has been restructured in such a way as to emphasize "... more clearly the central idea on which inferential methods are based: The value of any statistic ... will in general vary when sample after sample is selected from the population." In Chapter 7, the presentation on normal tolerance intervals has been expanded, and the Agresti-Coull score interval has been added. One-sided and two-sided con dence and prediction intervals have been grouped together for a more complete and concise treatment in Chapter 7.

Statistical package output from Minitab and SAS, and to a lesser extent from S-Plus and JMP, is provided for each chapter. Emphasis has been placed on p-values and their interpretation, rather than on critical values and regions, throughout the text. Since most students will utilize statistical software once they are nished with the course, stressing the concept and interpretation of p-values is important.

Many examples have been updated and new exercises have been included that use real-world data from various sources and disciplines. A data CD is provided with the text and can also be found at the website www.duxbury.com/datasets.htm. The datasets are provided in several formats including Excel, Minitab, JMP, and ASCII.

Dr. Devore continues to provide a quality product that can be used as a textbook or as a reference book. The fifth edition will continue to be a competitive textbook providing an excellent introduction to probability and statistics.

**Prentice-Hall, Inc.**, One Lake Street, Upper Saddle
River, NJ 07458; (800) 282-0693; Fax (800) 835-5327; www.prenhall.com