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, Incomplete block, Fractional factorial, response surface, 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.
Spring 2020 Syllabus
Topics Covered:Statistical analysis; Single-factor; Factorial; Nested; Latin-square; 2 to the f; Incomplete block; Fractional factorial; Response Surface; 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:Eight assignments accepted via blackboard
Projects:A required project will be assigned covering the design of an experiment, analysis, and iterpretation of results summarized in a short report and will be due during finals week. This may pertain to other work or research being performed or may be hypothetical. Data can be real or simulated.
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.
Design and Analysis of Experiments, 8th or 9th Edition, Wiley, ISBN: 9781119320937