1. Subject Name: Design of experiments L-T-P: 3-0-0
2. Pre-requisites: Probability and Statistics, Statistical Inference

Syllabus:

• The Analysis of Variance
• Randomized Block & Latin Square design
• Factorial design (2k with block)
• Incomplete and Confounded Block Designs
• 3^k and Fractional Factorial Design
• Response Surface Methods and Designs
• Experiments with Random Factors
• Nested and Split-Plot Designs
• Optimal design
• Robust Parameter Design Experiments
• Sequential design
• Response adaptive design

Reference Books:

1. Montgomery, D. C. (2017). Design and analysis of experiments. John Wiley & sons.
   1. Notes for the same
2. Lawson, J. (2014). Design and Analysis of Experiments with R(Vol. 115). CRC press.
3. Dean, A., Voss, D., & Draguljić, D. (1999). Design and analysis of experiments (Vol. 1). New York: Springer.
4. Cox, D. R., & Reid, N. (2000). The theory of the design of experiments. CRC Press.
5. Bapat, R. B. (2012). Linear algebra and linear models. Springer Science & Business Media.
6. Atkinson, A., Donev, A., & Tobias, R. (2007). Optimum experimental designs, with SAS (Vol. 34). Oxford University Press.
7. Ronald A. Fisher (1974), The Design of Experiments

More Resources

1. Swayam Prabha, IITK, Design of Experiments
2. Berkely Statistics Lab

Lecture-wise break-up:

The Basic Principles of DOE

1. Randomisation
2. Replication
3. Blocking
4. multi-factor designs
5. confounding

Review

Two sample t-test

• both samples come from normal population
• transformations to give same variance
• z-statistic is the difference between the sample means divided by the true population variance of the sample means