As the first step in the decommissioning of sasCommunity.org the site has been converted to read-only mode.
Here are some tips for How to share your SAS knowledge with your professional network.
Analyzing and Interpreting Continuous Data Using JMP: A Step-by-Step Guide
Title: Analyzing and Interpreting Continuous Data Using JMP: A Step-by-Step Guide
Click the watch tab to be notified when this page changes.
Based on real-world applications, Analyzing and Interpreting Continuous Data Using JMP: A Step-by-Step Guide, by Jose Ramirez, Ph.D., and Brenda S. Ramirez, M.S., combines statistical instructions with a powerful and popular software platform to solve common problems in engineering and science. In the many case studies provided, the authors clearly set up the problem, explain how the data were collected, show the analysis using JMP, interpret the output in a user-friendly way, and then draw conclusions and make recommendations. This step-by-step format enables users new to statistics or JMP to learn as they go, but the book will also be helpful to those with some familiarity with statistics and JMP. The book includes a foreword written by Professor Douglas C. Montgomery.
- starts with a description of a real problem from engineering or science including semicondutor, chemistry, mechanical and civil engineering.
- a 7-step problem-solving framework to make sure that the right problem is being solved with an appropriate selection of tools.
- The step-by-step instructions show how to use JMP to solve a particular problem, putting emphasis on how to interpret and translate the output in the context of the problem being solved.
As with the NBS Handbook 91, our main audience is you the engineer or scientist who needs to use or would like to use statistical techniques to help solve a particular problem. Each chapter is application driven, and is written with different objectives depending on your needs:
- For those of you who want a quick reference for how to solve common problems in engineering and science using statistical methods and JMP, each chapter includes step-by-step instructions for how to carry out the statistical techniques, interpret the results in the context of the problem statement, and draw the appropriate conclusions.
- For those of you who want a better understanding of the statistical underpinnings behind the techniques, each chapter provides a practical overview of the statistical concepts and appropriate references for further study.
- For those who want to learn how to benefit from the power of JMP in the context described previously, each chapter is loaded with general discussions, specific JMP step-by-step instructions, and tips and tricks.
"The genesis of the Ramirez work is the legendary NBS Handbook 91 Experimental Statistics 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 finest 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 first published paper of a young scientist named Einstein.
The book will also serve as a valuable supplement to traditional engineering/scientific 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
Additional Information (blog, downloads, podcast)
Visit the companion site for this book.
Check out our blog Stat Insights for out reflections on statistics as a catalyst for engineering and scientific discoveries.
Download the furnace qualification data from our January 12, 2010 webinar.
Listen to the podcast.
See the paper Statistical Intervals: Confidence, Prediction, Enclosure which is based on Chapter 2 of the book.
If you have any questions, feel free to email Jose.