Design and Analysis of Experiments (351-0-20)
Instructors
Arvind Krishna
Meeting Info
Harris Hall L07: Tues, Thurs 3:30PM - 4:50PM
Overview of class
The course will be a combination of the traditional physical experimental design and the more recently developed computer experimental designs. It will connect the design theory to application. You will be expected to understand and derive theoretical results, use the design theory to propose an appropriate design for a given scenario, analyze and interpret results. We will use the R programming language to generate designs, perform simulations, and calculate performance metrics.
Registration Requirements
Basic probability and statistics course such as STAT 320-1 or STAT 383-0 or MATH 310-1 or MATH 311-1 or MATH 314-0 or MATH 385-0 or ELEC_ENG 302-0 or IEMS 302-0 or equivalent. It will be good to have knowledge of regression.
Learning Objectives
By the end of the class students are expected to (1) understand design theory and derive theoretical results; (2) compare and contrast designs based on the theory, (3) develop and propose the most appropriate design for a given scenario; (4); analyze and interpret results after the design is used to perform experiments (5) use the R programming language to generate designs, perform simulations, calculate performance metrics, and analyze results, (6) translate a design problem from layman terms to technical terms and propose a solution.
Teaching Method
Lecture & Q&A during class. There will be a take-home quiz at the end of every lecture, which will be due before the beginning of the next lecture. Students will be required to attend class.
Evaluation Method
Homework will be assigned weekly or biweekly (about 5-6 assignments), one midterm exam, one final exam, attendance and quizzes.
Class Materials (Required)
The Design and Analysis of Computer Experiments (Springer Series in Statistics), 2nd ed. 2018 Edition, by Thomas J. Santner, Brian J. Williams, and William I. Notz, ISBN-13: 978-1493988457
Design and Analysis of Experiments by Montgomery (8th Edition, 2013), ISBN-13: 978-1118146927.
Experiments: Planning, Analysis, and Optimization 3rd Edition, by C.F. Jeff Wu and Michael S. Hamada (ISBN-13: 978-1119470106)
Class Materials (Suggested)
Lecture notes and R codes will be posted on canvas.
Class Notes
Computing: Statistical Software, R will be used to demonstrate the methodologies. Template R code will be posted on the course web page.
Class Attributes
Formal Studies Distro Area
Enrollment Requirements
Enrollment Requirements: Prerequisite: STAT 320-1 or STAT 383-0 or MATH 310-1 or MATH 311-1 or MATH 314-0 or MATH 385-0 or ELEC_ENG 302-0 or IEMS 302-0 or equivalent.