01448 – ChE 408 – Engineering Experimental Design - 3 credits

01464 – ChE 690 – Fundamentals of Chemical Engineering Experimentation - 3 credits

Spring 2007 Syllabus

InstructorText & Software - Learning Outcomes - Course Philosophy - Grading - Homework - Exams - Absences - Academic IntegrityCourse Schedule

 

Instructor (Return to top)

Dr. Valerie Young; 174 Stocker Center; 593-1496; valy@bobcat.ent.ohiou.edu

Dr. Young has office hours Tuesdays and Thursdays 2:00 - 4:00. Sometimes, professional obligations make it impossible to hold these hours sacred.  Please consult the weekly schedule outside her door, and sign up a day in advance for any other open time if you wish.  Also, if Dr. Young's door is open, you can ask her for time on-the-spot.  If Dr. Young's door is closed, then either she is not there or she is working to meet a deadline, and you should either sign up for an open time on the schedule outside her door, or come back later.  Dr. Young is not reliable about answering e-mail outside working hours.

Text and Software (Return to top)

The text for the course is P.R. Nelson, M. Coffin and K.A.F. Copeland, Introductory Statistics for Engineering Experimentation, Elsevier Academic Press, 2003.  This book shows output from Minitab, a statistics software package, in some examples.  Minitab is widely used in industry and is convenient for statistical analysis.  However, Excel and Matlab are capable of performing many of the same functions (although sometimes not as conveniently).  I will teach you how to do some basic statistics with Excel and Matlab; I expect you to figure out more advanced stuff as we go through the course.  You are not required to purchase Minitab.  Minitab is not provided in the department or college computer labs.  Minitab will not be required to complete any assignment in this course.

If you think you would like to try Minitab, go to www.minitab.com.  You can rent or buy Minitab at a reduced rate for students.  It costs several hundred dollars in the real world.

A neat online resource for help learning statistics is http://www.seeingstatistics.com.  This is an online textbook with lots of Java applets to help you understand statistics.  You are supposed to have to buy it to access it.  It is from Duxbury Press.  ISBN 0-534-37090-X.

I have also found the following books to be useful:

J.R. Taylor, An Introduction to Error Analysis:  The Study of Uncertainties in Physical Measurements, University Science Books, Sausilito, 1997.  ISBN 0-935702-75-X.  This is the best introduction I have found, but it does not go beyond the basics.  I ruled it out as a course text because it doesn’t include Statistical Process Control or Experimental Design.

W.P. Gardiner, Statistical Analysis Methods for Chemists:  A Software-based Approach, The Royal Society of Chemistry, Cambridge, 1997.  ISBN 0-85404-549-X.  This book is very practical and applied.  It shows you how to use Excel for most of your statistical analysis.  But, it can take some hunting to get it, it is expensive (in the U.S.) for a paperback, and it doesn’t have anything in it about Statistical Process Control.

D.H. Voelker, P.Z. Orton and S.V. Adams, CliffsQuickReview Statistics, Hungry Minds, New York, 2001.  ISBN 0-7645-6388-2.  This is only about $10 and you may find it really useful, particularly as a reference later on (like in Unit Operations Laboratory).

R.J. DelVecchio, Understanding Design of Experiments, Hanser/Gardner, Cincinnati, 1997.  ISBN 1-56990-222-4.  This is probably not a book you want now, but one you might want later if you need to understand this experimental design stuff a lot better in your real job.  It gives more complete coverage of the topic.

Course Philosophy (Return to top)

In this course, the responsibility for learning will fall very much on you. This will prepare you for professional life, when you will be expected to search for answers yourself, rather than waiting for someone to impart wisdom through lecture. My task will be to direct your learning.

I expect you to read the textbook.  Often, the textbook reading provides the background necessary for the in-class project, and lecture on the topic will come later.  This scheduling decision is based on sound pedagogical principles.  It has been proven that students learn best if they read on their own first to become familiar with the topic, then actively engage in some practical application of the topic,  then cover the theory in a lecture setting with an opportunity for questions.  I have tried to follow a pattern of Reading – Project – Lecture to maximize your learning.  Please help by doing the reading.  When you see “Read Ch. 7 in text” on the course schedule, it means you should read Chapter 7 before the next class meeting.  My lectures will not generally repeat the book; you can read the book.  In lecture, I will try to use a different approach to the same topic that is covered in the book.  Reading, lecture, homework, and in-class projects are all different ways to help you meet the course learning outcomes.

Statistics includes specialized terminology and funny symbols, but engineers are used to specialized terminology and funny symbols.  I think that some people find statistics challenging because there may be more than one reasonable way to solve the problem, and you have to pick one way and be able to justify it and explain it.  In this course, we will emphasize asking specific questions, identifying statistical techniques to help us answer those questions, and communicating the results.  We'll usually let the software (Excel, Matlab) handle the plug-and-chug.  

Grading (Return to top)

Homework (5 @ 50 points each)

250 points

Exam 1

200 points

Exam 2

200 points

Final exam

400 points

Total

1050 points

I do not grade "on the curve". There is no predetermined number of A's or F's in my class. No one will receive a grade lower than the percentage of points that they earn.  I do my best to make sure that the points earned on each graded assignment are consistent with the student's achievement of the course learning outcomes being assessed.   Passing this course should correlate well with showing competence.  To pass, you must demonstrate that you have achieved competence.  Do not count on "beating the average".  If you have questions about how a particular assignment relates to the learning outcomes for the course, please ask.  It is not my intention to assign "busy work". 

Percentage

Letter Grade

Interpretation

90 - 100

A- / A

Excellent, superb, extraordinary.  Mastery of most learning outcomes. 

80-89.999

B- / B / B+

Very good.  Consistent competence in most learning outcomes, and mastery of some.

70 - 79.999

C- / C / C+

Solid, acceptable performance.  Consistent competence in most learning outcomes.

60 - 69.999

D- / D / D+

Below expectations.  Competence in most learning outcomes shown at some point, but not consistent.

< 60

F

Poor or incomplete performance.  Competence in several learning outcomes not demonstrated.

  Homework and Practice Problems (Return to top)

Homework is due at the beginning of class on the due date.  Late homework incurs a penalty of 10% per business day.  If serious illness or a family emergency prevents you from submitting the homework, notify me immediately and I will make reasonable accommodation.  In case of an absence due to an interview, trip, appointment, or other foreseeable circumstance, you should submit your homework by the deadline.  Homework will always be accepted early. 

A memo will be required for most homework assignments, and the quality of your technical communication will be graded.  If technical communication in English is a challenge for you, please start your assignments early, and come to my office to discuss your draft memo.

You may talk to other students about the homework. However, each of you should do the homework yourself and turn in your own assignment. Plagiarism may result in a zero for the assignment or an F for the course.  Please refer to the Ohio University Student Handbook for guidelines on academic dishonesty.

In addition to the homework, which will be graded, I recommend doing a lot of "practice problems" to learn the material.  The graded homework and in-class exercises alone will probably not be sufficient.  The textbook contains suitable practice problems at the end of each section and at the end of each chapter.  You can and should work in groups to do these.  

Exams (Return to top)

All exams will be cumulative, open-book and open-notes.  Material from the text, lecture, homework, and in-class projects is fair game.  If you are wondering what will be emphasized, check out the course learning outcomes.  There will be no unannounced quizzes.

Absences (Return to top)

I do not require attendance at lecture or recitation.  Absences from exams will be handled in accordance with the policies in the Ohio University student handbook; please see me to arrange a makeup.

Academic Integrity and Professional Behavior (Return to top)

Engineering is a profession, and integrity is expected of professionals. Any action that deceives your professor about your achievement on a graded assignment or that interferes with learning opportunities for your classmates is unethical and will not be tolerated. Academic dishonesty is defined in the student handbook and will be dealt with according to the guidelines therein.

As an engineer, it is important that you get in the habit of behaving professionally.  I will expect professional behavior from you.  I will inform you when your behavior is unprofessional, and I may ask you to leave the room if you do not intend to change your behavior.  I will endeavor always to do this in a positive fashion and without embarrasing you, so long as I perceive on your part an honest attempt to meet the expectations of the profession.  

I believe that when both the instructor and the students are committed to learning, academic integrity will follow naturally.  Part of a commitment to learning is a commitment to the honest assessment of achievement.  I have found that it is helpful to reaffirm such a commitment regularly.  On graded work, I will include the following pledges.

Faculty Pledge:  To the best of my ability, I designed and will grade this work to accurately assess each student’s progress towards the outcomes of this course.
Student Pledge:  Knowing that this graded work should represent my individual progress towards the outcomes for this course, I have neither accepted nor given unauthorized assistance to complete it.
 
I will sign the faculty pledge on graded work to signify my commitment.  I cannot compell you to sign the student pledge, but I will be disappointed if you feel unable to make such a commitment. 

·Send mail to Dr. Young: valy@bobcat.ent.ohiou.edu.

·Return to top of syllabus.

(Last modified on 03/23/07)