|Program||Bachelor [학사과정]||Course Type||Major Elective [ 전공선택 ]|
|Course Code||31.342||Course No||IE342|
- Thu: 13:00~15:45
|Course Title||Regression Analysis and Experimental Designs [ 회귀분석 및 실험계획법 ]|
Tue: 14:30~16:00 / (E2)Industrial Engineering & Management Bldg. [ (E2)산업경영학동 ] (1122)
Thu: 14:30~16:00 / (E2)Industrial Engineering & Management Bldg. [ (E2)산업경영학동 ] (1122)
|Department||산업및시스템공학과(Department of Industrial & Systems Engineering)|
|Syllabus File||IE342_Regression Analysis and Experimental Designs_Syll_2020 Fall.pdf|
|Summary of Lecture||The course objective is to learn how to plan, design and conduct experiments efficiently and effectively, and analyze the resulting data to obtain objective conclusions. Both experimental design and statistical analysis issues are discussed. Opportunities to use the principles taught in the course arise in all phases of engineering and scientific work, including new product design and development, manufacturing and service process improvement, and technology development. Applications from various fields of engineering will be illustrated throughout the course.
Interesting lab sessions will provide students with the opportunity to gain hands-on experience on experimental design and data analysis. Computer software packages (such as Minitab or SPSS) to implement the methods presented will be illustrated extensively, and you will have opportunities to use it for homework assignments and the group lab reports.
|Material for Teaching||Textbook:
Design and Analysis of Experiments, 10th edition, by D.C. Montgomery, John Wiley & Sons, New York, 2019.
|Evaluation Criteria||* The followings evaluation criteria may change:
Class Participation & Individual Assignments: 25%
Labs and Reports (Team-based): 15%
Midterm Exam: 30%
Final Exam: 30%
|Lecture Schedule||Course Orientation; Introduction to Experimental Design
Simple Comparative Experiments (I)-Unpaired
Simple Comparative Experiments (II)-Paired
Comparative Experiments with 2+ Levels (I)- Completed Randomized Design (CRD)
Comparative Experiments with 2+ Levels (II)-Multiple Comparisons, Residual and Model Adequacy Check
Randomization, Replication and Blocking
Randomized Complete Block Design (RCBD)
Case Study and Discussion
Latin Squares Designs
Factorial Designs (I)
Factorial Designs (II)
Lab #1: Best Design for Paper Airplanes
The 2K Factorial Design (I)
The 2K Factorial Design (II)
Blocking and Confounding in The 2K Factorial Design
Lab #2: Catapult Projectile Motion
The 2k-p Fractional Factorial Design (I)
The 2k-p Fractional Factorial Design (II)
Regression Analysis (I)-Correlation analysis
Regression Analysis (II)-Linear and Nonlinear Regression analysis
Other Advanced Topics
|Memo||Prerequisites: Students should have a basic working knowledge of statistical methods.
Online classes (Real-time distance class using ZOOM) will be implemented for this course due to COVID-19 pandemic.