Design of Experiments
Learning Objective:A basic and broad understanding of experimental design.
Description:A thorough and practical course in design and analysis of experiments for experimental workers and applied statisticians. SAS statistical software is used for analysis. Taken by graduate students from many fields.
Topics Covered:Design fundamentals; completely randomized design, randomized complete blocks; latin square; multiclassification; factorial; nested factorial; incomplete block and fractional replications for 2n; 3n; 2m 3n, confounding; general mixed factorials; split plot; analysis of variance in regression models; optimum design.
Prerequisites:Purdue STAT 512 Applied Regression Analysis or equivalent; previous knowledge of SAS not required but helpful; knowledge of regression and linear models helpful.
Applied / Theory:70 / 30
Web Content:Notes, schedule, course information, handouts, homework, data sets, grades, SAS files, textbook errata.
Homework:See webpage for problems and due dates.
Projects:No project required.
Exams:Two midterm exams. Both exams are given with time limits (class period).
Textbooks:Official textbook information is now listed in the Schedule of Classes. NOTE: Textbook information is subject to be changed at any time at the discretion of the faculty member. If you have questions or concerns please contact the academic department.
Tentative: Design and Analysis of Experiments by M. Zhu; Montgomery and Douglas, 8th edition (ISBN: 978-1-1181-4692-7)