Statistical Case Studies Instructor Edition: A Collaboration Between Academe and Industry (ASA-SIAM Series on Statistics and Applied Probability)

315 Pages·1987·28.43 MB·English

by  Roxy Peck

Statistical
Case Studies
ASA-SIAM Series on
Statistics and Applied Probability
SSIAMUAN ASA
IVAM
The ASA-SIAM Series on Statistics and Applied Probability is published jointly by SI/\IVIheAsa-SIam Series on Statistics and Applied Probability is published jointly by
the American Statistical Association and the Society for Industrial and Applied Mathematics. The
series consists of a broad spectrum of books on topics in statistics and applied probability. The
purpose of the series is to provide inexpensive, quality publications of interest to the intersecting
membership of the two societies.
Editorial Board
Donald P. Gaver Andrew Solow
Naval Postgraduate School, Editor-in-Chief Woods Hole Oceanographic Institution
Alan F. Karr Werner Stuetzle
Mational Institute of Statistical Sciences University of Washington
John Lehoczky Grace Wahba
Carnegie Mellon University University of Wisconsin
Robert L. Mason Eric Ziegel
Southwest Research Institute Amoco Corporation
Robert Rodriguez
SAS Institute
Peck, R., Haugh, L D., and Goodman, A., Statistical Case Studies: A Collaboration Between Academe
and Industry, Student Edition
Peck, R., Haugh, L. D., and Goodman, A., Statistical Case Studies: A Collaboration Between Academe
and Industry
Barlow, R. E., Engineering Reliability
Czitrom, V. and Spagon, P. D., Statistical Case Studies for Industrial Process Improvement
Statistical
Case Studies
A Collaboration Between
Academe and Industry
Roxy Peck
California Polytechnic State University
San Luis Obispo, California
Larry D. Haugh
University of Vermont
Burlington, Vermont
Arnold Goodman
University of California
Irvine, California
ASA
Society for Industrial and Applied Mathematics American Statistical Association
Philadelphia, Pennsylvania Alexandria, Virginia
© 1998 by the American Statistical Association and the Society for Industrial and Applied
Mathematics.
10987654321
All rights reserved. Printed in the United States of America. No part of this book may be
reproduced, stored, or transmitted in any manner without the written permission of the
publisher. For information, write to the Society for Industrial and Applied Mathematics,
3600 University City Science Center, Philadelphia, PA 19104-2688.
Partial support for this work was provided by the Undergraduate
Faculty Enhancement program at the National Science Foundation under
DUE 9455055. The work is that of the authors and does not necessarily
express the views of the NSF.
ISBNO-89871-413-3
is a registered trademark.
In memory of Joyce Curry-Daly, statistics educator extraordinaire.
Roxy Peck
For my wonderful family: Janie, Wendi, Josh, and Jeremy.
Larry Haugh
Honoring Herman Chernoff's distinguished contributions
and unique personal style on his recent retirement:
he shaped my thinking that led to Interfaces
and his Faces were 20 years ahead
of the computer visualization.
Arnie Goodman
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CONTENTS
Preface ix
Introductions
The Benefits of Cases xv
William C. Parr
Partnering for the Future of the Statistics Profession xix
Ronald L. Iman
Chapter 1: Are the Fish Safe to Eat?
Assessing Mercury Levels in Fish in Maine Lakes 1
Jennifer A. Hoeting and Anthony R. Olsen
Chapter 2: Chemical Assay Validation 15
Russell Reeve and Francis Giesbrecht
Chapter 3: Automating a Manual Telephone Process 25
Mary Batcher, Kevin Cecco, and Dennis Lin
Chapter 4: Dissolution Method Equivalence 37
Russell Reeve and Francis Giesbrecht
Chapter 5: Comparison of Hospital Length of Stay Between
Two Insurers for Patients with Pediatric Asthma 45
Robert L. Houchens and Nancy Schoeps
Chapter 6: Comparing Nonsteroidal Anti-inflammatory Drugs
with Respect to Stomach Damage 65
Tom Filloon and Jack Tubbs
Chapter 7: Validating an Assay of Viral Contamination 77
Lawrence I-Kuei Lin and W. Robert Stephenson
Chapter 8: Control Charts for Quality Characteristics
Under Nonnormal Distributions 89
Youn-Min Chou, Galen D. Halverson, and Steve T. Mandraccia
Chapter 9: Evaluation of Sound to Improve Customer Value 99
John R. Voit and Esteban Walker
Chapter 10: Improving Integrated Circuit Manufacture
Using a Designed Experiment 109
Veronica Czitrom, John Sniegowski, and Larry D. Haugh
vii
viii Contents
Chapter 11: Evaluating the Effects of Nonresponse and the Number
of Response Levels on Survey Samples 129
Robert K. Smidt and Robert Tortora
Chapter 12: Designing an Experiment to Obtain a Target Value
in the Chemical Processes Industry 143
Michael C. Morrow, Thomas Kuczek, and Marcey L. Abate
Chapter 13: Investigating Flight Response of Pacific Brant
to Helicopters at Izembek Lagoon, Alaska
by Using Logistic Regression 155
Wallace P. Erickson, Todd G. Nick, and David H. Ward
Chapter 14: Estimating the Biomass of Forage Fishes in Alaska's
Prince William Sound Following
the Exxon Valdez Oil Spill 171
Winson Taam, Lyman McDonald, Kenneth Coyle, and Lew Halderson
Chapter 15: A Simplified Simulation of the Impact of Environmental
Interference on Measurement Systems in an Electrical
Components Testing Laboratory 185
David A. Fluharty, Yiqian Wang, and James D. Lynch
Chapter 16: Cerebral Blood Flow Cycling:
Anesthesia and Arterial Blood Pressure 203
Michael H. Kutner, Kirk A. Easley, Stephen C. Jones, and G. Rex Bryce
Chapter 17: Modeling Circuit Board Yields 217
Lorraine Denby, Karen Kafadar, and Tom Land
Chapter 18: Experimental Design for Process Settings
in Aircraft Manufacturing 235
Roger M. Sauter and Russell V. Lenth
Chapter 19: An Evaluation of Process Capability
for Fuel Injector Process
Using Monte Carlo Simulation 247
Carl Lee and Gus A. D. Matzo
Chapter 20: Data Fusion and Maintenance Policies
for Continuous Production Processes 267
Nozer D. Singpurwalla and Joseph N. Skwish
Index 279
PREFACE
If you only have pretend data, you can only pretend to analyze it.
George Cobb
As professors of statistics we tell our students that an understanding of research
questions is necessary in order to collect meaningful data and analyze it intelligently.
"Don't collect data first and then try to figure out what (if anything) you can do with it," we
admonish students and also researchers who come to us for help with data analysis. Yet
when we teach statistics courses, we often do just that! Now convinced of the necessity to
include examples that use REAL data, we search for real data sets and then try to come up
with some question that we think might in some way capture our students' interest.
Without an in-depth understanding of how the data was collected or why it is important, we
look at data and try to figure out what (if anything) we can do with it to turn it in to a
classroom example. I confess that I am guiltier of this than most—I have created whole
textbooks full of examples and exercises in just this way.
While examples and case studies of this type are certainly better than those based on
artificial data and contrived situations, I now realize that a case study based on real data
from industry that has research questions and directed analyses constructed by an academic
often looks very different from a case study based on actual practice in industry.
Traditional statistics education has been criticized for not adequately preparing statisticians
and engineers for careers in industry and for being unresponsive to the needs of industry.
This may be partially due to the fact that most university faculty do not have the type of
industry experience that would enable them to easily incorporate examples based on actual
practice in industry into their courses. We hope that this collection of case studies can help
make this easier.
The collection of cases is eclectic—they come from a variety of application areas and
the vast majority require the use of multiple data analysis methods. Some are challenging
and some are messy—we have made no effort to "simplify" the problems presented for
classroom use. What unifies this collection is that all are based on actual practice in
industry or government.
Each case study in this collection is the product of a collaboration between statisticians
in industry and colleagues in academe. These collaborations were made possible by
support from the National Science Foundation's Division of Undergraduate Education
through an Undergraduate Faculty Enhancement grant. Forty-four statisticians, 22 from
academic institutions and 22 from business, government, and industry, participated in the
Collaboration Project and in the development of these case studies. All participants met at
a workshop held at Cal Poly, San Luis Obispo, during the summer of 1995. The workshop
program focused on academe-industry partnerships and included presentations by Ron
Iman, Bill Parr, Bob Mason, and Dick Gunst. Academe-industry pairs were also formed
during this workshop. During the following academic year, each pair participated in three-
day exchange site visits. These site visits enabled each participant to experience the work
environment of his or her partner and became the basis for the development of the case
studies that make up this collection. Twenty-one of the 22 pairs produced a case study
(one pair produced three), and 20 of the 24 cases submitted are included in this volume.
The result of these individual collaborations is a collection of case studies that illustrate
real application of statistical methodology to solve problems in industry. They address
problems important to industry, as opposed to an academic view of what might be
important. As a collection, they show the scope and variety of problems that can be
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