The objective of this course is to provide students with knowledge in experimental design and corresponding methods of data analysis. This course will cover CRD, RCBD, factorial designs
(fixed, mixed and random models), nested designs, split-plot Design, cross over design, repeated measurement, analysis of covariance, incomplete block design,
and fractional factorial design. Students also learn SAS coding for analyzing data.The objective of this course is to provide students with knowledge in experimental design and corresponding methods of data analysis. This course will cover CRD, RCBD, factorial designs
(fixed, mixed and random models), nested designs, split-plot Design, cross over design, repeated measurement, analysis of covariance, incomplete block design,
and fractional factorial design. Students also learn SAS coding for analyzing data.
The subject of experimental design is important due to its widespread use in many areas of scientific research. The topic of this course will include introduction of the principles of experimental designs and randomization, the process of design and corresponding analysis of variance. We shall introduce many important designs, such as completely randomized design, randomized block design, Latin type design, nested design, factorial design, incomplete design, split-plot design, cross over design, and response surface design. It is essential that students obtain a firm understanding of the philosophical basis and of the principles of experimental design as well as a broad knowledge of available designs together with their assumptions and application. The students also need to learn SAS coding to analyze data from various designs.
The subject of experimental design is important due to its widespread use in many areas of scientific research. The topic of this course will include introduction of the principles of experimental designs and randomization, the process of design and corresponding analysis of variance. We shall introduce many important designs, such as completely randomized design, randomized block design, Latin type design, nested design, factorial design, incomplete design, split-plot design, cross over design, and response surface design. It is essential that students obtain a firm understanding of the philosophical basis and of the principles of experimental design as well as a broad knowledge of available designs together with their assumptions and application. The students also need to learn SAS coding to analyze data from various designs.
1. Design of Experiments : Statistical Principles of Research Design and Analysis.
(2nd Edition), by Robert, O. Kuehl
1. design of experiments: statistical principles of research design and analysis.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| midtermmidterm midterm |
50 | |
| finalfinal final |
50 |
