Industrial Applications of Statistics
Learning Objective:The application of statistics to the design and analysis of experiment-based industrial studies in order to optimize targeted objectives.
Design of experiments and analysis of experimental results are covered in depth. These include Single-factor, Factorial, Nested, Latin-square, 2 to the f, 3 to the f, Incomplete block, Fractional factorial, and Taguchi designs. Depending on the context, an appropriate design can be chosen in order to minimize the costs for the experiment while gathering sufficient data to achieve undiscovered knowledge. This course will be application-oriented.
Topics Covered:Statistical analysis; Single-factor; Factorial; Nested; Latin-square; 2 to the f; 3 to the f; Incomplete block; Fractional factorial; Taguchi.
Prerequisites:An introductory statistics course that covers basic probability, estimation, hypothesis testing, and simple regression.
Applied / Theory:70 / 30
Web Content:Blackboard course page will include the syllabus, lecture notes, homework assignments and grades. Piazza discussion board will be also be used.
Homework:Roughly ten assignments. Accepted via Blackboard.
Projects:A required project will be assigned. For off-campus students or students involved in research, they can select their own project topic. For those who do not have a topic, a project will be assigned.
Exams:Two (one-hour 15 minutes) midterm exams; no final exam.
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: Required - Charles R. Hicks, "Fundamental Concepts in the Design of Experiments" 5th edition, Oxford University Press, ISBN:9780195122732.