MATH 586 Fall 2006

Instructor: Dr. Surajit Ray
Department of Mathematics and Statistics
MCS 222, 111 Cummington Street, Boston, MA 02215
Phone: (617) 353-5209, Fax: (617) 353-8100

Courseinfo Login ( BU Students)

[ Document Icon ] Course Goals
At the end of the course students should develop a deep understanding of the importance of Design for any scientific experiment. In particular one should have detailed knowledge of Randomized blocks, Latin and Graeco-Latin squares, factorial arrangements with confounding and fractional replication, split-plot, crossover, and response surface designs. Treatment of missing data, group sizes, relative efficiency, and relationship between design and analysis will also be discussed.

Students should also be able to use one software package ( R/Minitab/SAS) for constructing experimental designs and analyzing data collected using those designs.

[ Document Icon ] Syllabus
0. Basic principles and introduction to regression analysis (Chapter 2)

1. Experiments with a single factor, analysis of variance (Chapter 3)

2. Experiments with more than one factor, blocking, Latin squares, analysis of variance and covariance, random effects models, other analysis techniques (Chapeter 4)

3. General factorial design, analysis of 2k factorial design, confounding in 2k factorial design, 3k factorial design, nested factorial design, split-plot factorial experiment. (Chapter 5-8)

5. Three-level designs (Chapter 9)

6. Brief introduction to response surface methodology (Chapter 11)

[ Document Icon ] Text Book
Design and Analysis of Experiments, 6th Edition
Douglas C. Montgomery
ISBN: 0-471-48735-X
Hardcover
660 pages
December 2004
US $124.95 From Wiley | From Amazon

[ Document Icon ] Reference Books/Other readings
  1. Statistics for Experimenters: Design, Innovation, and Discovery, 2nd Edition
    by George E. P. Box, J. Stuart Hunter, William G. Hunter

  2. Experiments: Planning, Analysis, and Parameter Design Optimization
    by C. F. Jeff Wu, Michael Hamada

[ Document Icon ] Internet Resources
  • “An R companion to ‘Experimental Design’ ” by Vikneswaran (PDF).
  • “An Introduction to S and the Hmisc and Design Libraries” by Carlos Alzola and Frank E. Harrell, especially of interest to users of the Hmisc or Design packages, or R users interested in data manipulation, recoding, etc. (PDF)

[ Document Icon ] Grading Policies
HOMEWORK :Homework will be assigned regularly during the course and a due date will be announced. No late homework will be accepted. To receive full credit for your solutions of the homework problems, all works must be shown.

EXAMINATIONS: There will be two midterms and one final. Policy regarding the exams will be announced later. All exams are required and there will be no make up exam. Schedule of Exams will be announced later.

GRADE DISTRIBUTION
  • HOMEWORK 20%
  • MIDTERM I 25%
  • MIDTERM II 25%
  • FINAL 30%