Analyzing and Interpreting Continuous Data Using JMP:: A Step-by-Step Guide

489 Pages·2009·8.03 MB·English

by  Jose G. Ramirez Ph.D.

Praise from the Experts
“The genesis of the Ramírez work is the legendary Experimental Statistics, NBS
Handbook 91 assembled by Mary Natrella of the National Bureau of Standards (now
National Institute of Standards and Technology). The authors have skillfully blended one
of the fi nest traditional statistical works with the contemporary software capability of
JMP. The result is a powerful, yet user-friendly resource the practicing engineer/scientist
can rely upon to solve the immediate problem at hand.
“The authors are seasoned industrial statisticians responding to the needs of frontline
engineers and scientists. Unlike traditional textbooks, each chapter focuses upon a real
life technical problem rather than a statistical technique. The book is rich with many
examples across both industry and discipline.
“For example, both young and seasoned investigators will enjoy and appreciate the dynamic
JMP analysis of data from the fi rst published paper of a young scientist named Einstein.
“The book will also serve as a valuable supplement to traditional engineering/scientifi c
statistical textbooks at both the undergraduate and graduate level. The authors deftly
dovetail both graphical and computational analysis and in the process clarify and quantify
the industrial challenge under investigation.
“We look forward to utilizing the book in our next offering of engineering statistics.
“This book deserves a place on the bookshelf of every practicing engineer and scientist.”
James C. Ford Ph.D.
College of Engineering
University of Delaware

“Analyzing and Interpreting Continuous Data Using JMP: A Step by Step Guide, by
José G. Ramírez, Ph.D., and Brenda S. Ramírez, M.S., does a wonderful job blending
the practical side of industrial data with a rigorous statistical handling in an intuitive and
graphical framework utilizing JMP. Industrial engineers/scientists interested in proper
handling of statistical comparisons related to experimentation and calibration will fi nd
its step-by-step framework complete and well documented via detailed process steps,
examples, and visuals. This work provides a unique connection back to Experimental
Statistics, NBS Handbook 91 (now NIST SP 958). Lastly, the book is very much a ready-
for-use reference guide for common statistical problems in engineering and science.”
Tim Rey
Leader, Data Mining and Modeling
The Dow Chemical Company
“Analyzing and Interpreting Continuous Data Using JMP: A Step-by-Step Guide, by
José G. Ramírez and Brenda S. Ramírez, is not just an introductory guide to statistical
analysis; it is above all an excellent tool for quality and reliability engineers and for Six
Sigma practitioners. The authors have made data analysis and interpretation very easy
to do by using examples that are encountered on a daily basis in all industries. While
it is very instructive and covers just about all the subjects applicable to all aspects of
management, especially quality and reliability, the book keeps mathematical reasoning
to a strict minimum. The many examples and the graphs that accompany each chapter
make the book easier to understand by a wider audience. This is just an excellent book for
beginners and a reference for practitioners!”
Issa Bass
Senior Six Sigma Consultant with Manor House and Associates
Analyzing and Interpreting
Continuous Data Using JMP®
A Step-by-Step Guide
José G. Ramírez, Ph.D.
Brenda S. Ramírez, M.S.
The correct bibliographic citation for this manual is as follows: Ramírez, José G., and Brenda S. Ramírez.
2009. Analyzing and Interpreting Continuous Data Using JMP®: A Step-by-Step Guide. Cary, NC:
SAS Institute Inc.
Analyzing and Interpreting Continuous Data Using JMP®: A Step-by-Step Guide
Copyright © 2009, SAS Institute Inc., Cary, NC, USA
ISBN 978-1-59994-488-3
All rights reserved. Produced in the United States of America.
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1st printing, August 2009
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To our daughter Oriana Sofía
Our joyful “Golden Wisdom”
To Brittany, Lindsay, Harrison, Jadon, and Nehum
Future engineers and scientists
To Professor G.E.P. Box
Advisor, Mentor, Friend (“Pel”)

Contents
Foreword ix
Acknowledgments xi
Chapter 1 Using This Book 1
1.1 Origins of This Book 2
1.2 Purpose 3
1.3 Audience 3
1.4 Prerequisites 4
1.5 What’s Unique About This Book? 4
1.6 Chapter Contents 5
1.7 Chapter Layout 8
1.8 Step-by-Step Analysis Instructions 10
1.9 JMP Software 12
1.10 Scope 15
1.11 Typographical Conventions 17
1.12 References 21
Chapter 2 Overview of Statistical Concepts and Ideas 23
2.1 Why Statistics? 24
2.2 Measurement Scales, Modeling Types, and Roles 28
2.2.1a Nominal Scale 29
2.2.1b Ordinal Scale 29
2.2.1c Interval Scale 29
2.2.1d Ratio Scale 29
2.2.2 Which Scale? 30
2.2.3 Responses and Factors 31
2.3 Statistical Inference: From a Sample to a Population 34
2.3.1 Random Sampling 38
2.3.2 Randomization 42
vi Contents
2.4 Descriptive Statistics and Graphical Displays 44
2.5 Quantifying Uncertainty: Common Probability Distributions 55
2.5.1 Normal Distribution 59
2.6 Useful Statistical Intervals 65
2.6.1 Confi dence Interval for the Mean 67
2.6.2 Prediction Interval for One Future Observation 67
2.6.3 Tolerance Interval to Contain a Given Proportion p of
the Sampled Population 68
2.6.4 What Does Confi dence Level Mean? 71
2.7 Overview of Tests of Signifi cance 74
2.7.1 Critical Components of a Test of Signifi cance 75
2.7.2 A 7-Step Framework for Statistical Studies 77
2.8 Summary 79
2.9 References 79
Chapter 3 Characterizing the Measured Performance of a Material,
Process, or Product 81
3.1 Problem Description 82
3.2 Key Questions, Concepts, and Tools 83
3.3 Overview of Exploratory Data Analysis 85
3.3.1 Description and Some Applications 85
3.3.2 Descriptive Statistics 86
3.3.3 Graphs and Visualization Tools 93
3.3.4 Statistical Intervals 102
3.4 Step-by-Step JMP Analysis Instructions 104
3.5 Summary 148
3.6 References 149
Chapter 4 Comparing the Measured Performance of a Material,
Process, or Product to a Standard 151
4.1 Problem Description 152
4.2 Key Questions, Concepts, and Tools 153
4.3 Overview of One-Sample Tests of Signifi cance 155
Contents vii
4.3.1 Description and Some Applications 155
4.3.2 Comparing Average Performance to a Standard 156
4.3.3 Comparing Performance Variation to a Standard 165
4.3.4 Sample Size Calculations for Comparing Performance
to a Standard 170
4.4 Step-by-Step JMP Analysis Instructions 181
4.5 Testing Equivalence to a Standard 213
4.6 Summary 215
4.7 References 215
Chapter 5 Comparing the Measured Performance of Two Materials,
Processes, or Products 217
5.1 Problem Description 218
5.2 Key Questions, Concepts, and Tools 219
5.3 Overview of Two-Sample Signifi cance Test 221
5.3.1 Description and Some Applications 221
5.3.2 Comparing Average Performance of Two Materials,
Processes, or Products 223
5.3.3 What To Do When We Have Matched Pairs 232
5.3.4 Comparing the Performance Variation of Two Materials,
Processes, or Products 236
5.3.5 Sample Size Calculations 242
5.4 Step-by-Step JMP Analysis Instructions 248
5.5 Testing Equivalence of Two Materials, Processes, or
Products 286
5.6 Summary 289
5.7 References 290
Chapter 6 Comparing the Measured Performance of Several
Materials Processes, or Products 291
6.1 Problem Description 292
6.2 Key Questions, Concepts, and Tools 293
6.3 Overview of One-way ANOVA 295