Short Programs
Data and Models in Engineering, Science and Business, Part I [12.15s]
Date: July 19-20, 2010 | Tuition: $1,500
Overview | Learning Objectives | Course Materials | Who Should Attend | Schedule | Participants' Comments | On-Site Courses | Instructors | Updates
Special Package Offers
Combination Courses Package
Save $500 by taking both this course and Data and Models in Engineering, Science and Business, Part II [12.16s]. Combined tuition is $2,500. Apply for this package now »
Overview
A course for anyone wanting to fit data to models. Topics include linear least squares, non-linear least squares, singular value decomposition, sensitivity analysis, experiment design and parameter error estimation (Jackknife). Introduces principles leading to rapid application of methods. Includes pre-programmed computer exercises.
Fundamentals: Core concepts, understandings and tools (75%)
Latest Developments: Recent advances and future trends (25%)
Lecture: Delivery of material in a lecture format (40%)
Discussion: Guided discussion reinforcing lectures and computer lab work (15%)
Labs: Computer-based participatory learning (45%)
Introductory: Appropriate for a general audience (30%)
Specialized: Assumes experience in practice area or field (50%)
Advanced: In-depth explorations at the graduate level (20%)
Learning Objectives
- Examine how to fit data to models.
- Define linear least squares, non-linear least squares, singular value decomposition, sensitivity analysis, experiment design, and parameter error estimation.
- Investigate principles leading to rapid application of methods.
- Evaluate the results of pre-programmed computer exercises.
Course Materials
Lectures will be accompanied by copies of all presented material and additional published reviews. Participants are encouraged to study a basic text prior to attendance. Two suggestions are:
Data Reduction and Error Analysis for the Physical Sciences, P. R. Bevington and D. K. Robinson, McGraw-Hill, Inc., 2nd ed., 1992.
Applied Regression Analysis, N. R. Draper and H. Smith, John Wiley and Sons, Inc., 2nd ed., 1981.
Who Should Attend
Anyone who fits data to models. This course is truly broad-based and participants from vastly differing fields are envisioned and encouraged to attend. Some of these fields are engineering, business, natural sciences, geoscience, medicine, statistics, and economics. Familiarity with computing, linear algebra, and statistics is desirable.
Recent and past participants in this course have come from: Air Force Office of Scientific Research (AFOSR), Amgen Inc., AT&T, BAE Systems, Bank of America, Boeing, Boehringer Ingelheim Pharmaceuticals, BP America, Cox Communications, Delphi, Dupont, Environmental Protection Agency, ExxonMobil Chemical, General Motors, Hitachi (Japan), Intel, Johnson & Johnson, Korea Power Co., Kraft Foods, Los Alamos Labs, Mathworks, Mayo Clinic, Merck & Co Inc, Motorola, Naval Research Laboratory, NTT (Japan), Nokia Research Center, Phillips Exeter Academy, Pioneer Investments, Polaroid Corporation, Sandia National Labs, Saudi Arabian Monetary Agency (Saudi Arabia), University of Pennsylvania, University of West Indies (West Indies), US Air Force.
Course schedule and registration times
Class runs 9:00 am - 5:00 pm every day.
Registration is on Monday morning from 7:45 - 8:30 am.
Participants' Comments
Deputy Chief Scientist, Air Force Office of Scientific Research (AFOSR)
“The course efficiently provided a broad understanding of a wide variety of methods to a very varied and interesting group of students.”
Associate Professor, University of the Pacific
“Course was well designed. Lab work was very helpful. Application to real-world problems was well illustrated.”
Electrical & Controls Engineer, BP America
I enjoyed the courses taken at MIT this summer. They combined a large amount of theory with lab work in an accelerated fashion. These courses have been the best post-bachelors courses I have taken thus far."
Postdoctoral Research Fellow, Brigham and Women's Hospital
“I found it to be a very stimulating and exciting environment. I felt that the instructors were very knowledgeable in the area and were willing to discuss issues related to applications beyond the classroom. Overall, I would attend courses at the MIT Professional Education - Short Programs in the future and would recommend the program to colleagues.”
On-site Courses
We can also offer this course for groups of employees at your location. Please contact the Short Programs office for further details.
Instructors
Frank Dale Morgan obtained his BSc (Math/Physics, 1970) and his MSc (Theoretical Solid State Physics, 1972) from the University of the West Indies, Trinidad, where he was a Lecturer in Physics, 1970-1975. From 1975 to 1981, he completed a PhD in Geophysics at the Massachusetts Institute of Technology. He returned to the University of the West Indies, Trinidad, as a Research Fellow in the Seismic Research Unit. From 1983 to 1985 he was a Research Associate in the Geophysics Department at Stanford University. In 1985 he joined the faculty of the Geophysics Department at Texas A&M University. He is now a Professor of Geophysics at the Massachusetts Institute of Technology in the Department of Earth, Atmospheric, and Planetary Sciences and associated with the Earth Resources Laboratory. His current interests are in rock physics, geoelectromagnetism, applied seismology, inverse theory, environmental and engineering geophysics, electrochemistry and electronic instrumentation. He teaches courses on the physics and chemistry of rocks, environmental and engineering geophysics, alternative energy and inverse theory. He is the organizer and principal instructor for the course.
Updates
There are no updates at this time.
