STAT616  — Advanced Design of Experiments
Fall 2015


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Instructor:                  John D. Pesek, Jr.

                                    227 Townsend Hall


                                    E-mail: pesek at

                                    Web site


Time and Place:       Tuesdays 6:00-9:00 pm

                                    009  Townsend Hall


Office Hours:            By appointment


Texts:                          Required: SAS System for Mixed Models, Second Edition, Littell, Milliken, Stroup, Wolfinger and Schabenberger, SAS Institute, Cary, NC. 2006.

Required: Design and Analysis of Experiments. Angela Dean and Daniel Voss. Springer. 1999.


Computer:                 Either a Windows or Macintosh laptop will be required to do the inclass exercises. 


Prerequisites:           STAT615 and STAT602 and/or permission of instructor


Objective:                   Study the design and analysis of mixed and repeated measures
models using the mixed procedure of SAS along with related topics.

UNIVERSITY OF DELAWARE GENERAL EDUCATION GOALS: The objectives of this course align with the following General Education Goals (bolded):


Attain effective skills in (a) oral and (b) written communication, (c) quantitative reasoning, and (d) the use of information technology – By doing homework assignments, supportive reading and lab exercises. This involves analysis and computation, both by hand and using SAS software.

Learn to think critically to solve problems – By doing homework assignments and lab exercises. Both involve analysis and computation, both by hand and using SAS software.

Be able to work and learn both independently and
collaboratively – 
By doing independent homework assignments  and lab exercises in collaboration with a partner. Both involve analysis and computation, both by hand and using SAS software.


Course Requirements:


1.    In case class is cancelled because of bad weather or other contingencies, make up classes may be necessary. It may also be necessary to reschedule exams.


2.    On Tuesday, September 29, 2015 and Tuesday November 3, 2015 there will be exams for the first 90 minutes of the course. In the remainder there will be regular class. There will also be a final at a date to be announced. Important! The final and the exams must be taken at the scheduled time unless prior arrangements are made. There must be adequate cause in the judgment of the instructor.

Note: Plane reservations leaving before the final date are not considered adequate cause. 

Note: Attendance at a wedding is not adequate cause for taking exams at other times. This is regardless of whether you are getting married, you are a member of the wedding party, or you are just in attendance.

Note:  Having more than one final on the same day is also not adequate cause. 

Note: There are many legitimate reasons such as illness and family emergencies. Please contact me under those circumstances.

Note: Students with either learning and/or physical disabilities are entitled to special consideration according to university policy. To qualify for this consideration, the instructor must be given official notification of the disability from the appropriate university unit.

Both the midterm and the final will be cumulative.  Some questions on the exam will require the demonstration of lessons learned in class and in the homework while some will also require the resourceful use of that knowledge.  When preparing for exams, it is important to remember that in addition to using the skills acquired in class, it is also necessary to be able to decide which skills are needed for a particular problem.

I often give out practice exams. The primary purpose of the practice exam is to give you a chance to see the general structure of my exams. There is no guarantee that the questions will be the same or similar to questions on the practice exams. Because I have changed from a midterm to two exams this term there will be no practice exams for these two inclass exams but there will be a practice final.

3.    There are a number of homework assignments. Each assignment is due on a specific date to be announced.  The homework will not be graded and will not count directly toward your grade. It is highly advised that you do them to learn the material. Solutions will be posted after the due date and there will be opportunities in class and other times to ask questions about the homework.

4.    There will generally be at least one laboratory exercise per class. In general these will be done in groups of four. The purpose is to give you a chance to learn by doing. Credit is given for participation. In case an exercise is missed, students with a proper excuse will have their grade based on other work done. Otherwise a grade of zero will be recorded. Students are held responsible for all work covered and for meeting course deadlines. In general the lab exercise is due by 1:30pm the Thursday after class.

Note: Missing class in order to complete work for another class or to study for an exam in another class is not a proper excuse.

5.    During class students are expected to be respectful of each other and the instructor. It is especially important to respect your lab partners. Questions are welcome if they are germane to the current topic. Other questions are welcome when asked in private. In this class data will come from a variety of disciplines. It is natural to be most interested in data from your own field of study. However, respect and courtesy toward data from other disciplines are expected.

6.    Academic honesty is expected at all times (See the Student Guide to  University Policies for complete information on the Code of Student Conduct at

7.    In general students are expected to know and the university's policy on responsible computer use.

Grading Procedure:


The final course grade will be based upon the student’s performance on the exams and participation in the lab exercises. The exams will count 95 percent of the grade and participation in the lab exercises 5 percent of the grade.

Important information for listeners (official auditors). At the University of Delaware you may take a course as a listener. Then you are not required to take exams or turn in homework although you may do so. However, you ARE required to attend class. If a student has listener status and has a large number of unexcused absences, the instructor may give a grade of LW (for listener withdrawn) instead of L (for listener).  While an LW will not affect your GPA or your graduation, prospective employers are often concerned to see withdrawn courses on your transcript and it is best to avoid them.

Requests for score changes:


If you feel either an assignment or an exam deserves a higher score, you need to make a written request. The written request must be made on a separate sheet of paper and the assignment or exam must be attached. If you are still not satisfied, you may make an appointment with the instructor to discuss the matter. For Sakai assignments written requests may be made by the Sakai message system.  In this case there will be no need to include the assignment since I will have retained a copy.




Students are encouraged to visit the instructor in his office. Students may make appointments or drop by (in the last case the instructor may not always be available).  Students are also encouraged to communicate with the instructor using E-mail.



Announcements about the course will be made by e-mail. Students should pay close attention to e-mail messages from the instructor.




In general handouts will be available on Sakai in “pdf” format. Students are expected to download and print copies to have available in class.  Some handouts may still be provided in class. To access the handouts go to the URL  and log onto Sakai. Then go to stat616.



Topics to be covered (depending on time and interest of the class) are:


v  Review of design principles

Ø  Using tree diagrams to understand designs

Ø  Contrasts

Ø  Using Kronecker products (of matrices) to generate contrasts

v  Introduction to mixed models and repeated measures.

Ø  Fixed and random effects

Ø  Repeated measures with patterned covariance matrices

v  "Classical" Approaches to repeated measures (Greenhouse-Geisser and Huyhn-Feldt methods)

v  The mixed model equations

v  Satterthwaite and Kenward-Rogers degrees of freedom

v  BLUEs (Best Linear Unbiased Estimators) for fixed effects

v  BLUPs (Best Linear Unbiased Predictors) for random effects

v  Generalized linear mixed models

v  Power

v  Randomization

v  Examples such as

Ø  Block designs

Ø  Split plot and split-split plot designs

Ø  Longitudinal studies

Ø  Latin squares

Ø  Analysis of Covariance

Ø  Random Coefficient Models

Ø  Crossover designs

v  Other topics.

Ø  Computer aided design

Ø  Fractional factorial designs

Ø  Incomplete block designs