​CH5020 Statistical Design and Analysis of Experiments


This course is meant for students and research scholars who carry out extensive experiments as part of their academic programme requirements.  The fundamental concepts including random error, random variables, continuous probability distributions, random sampling and hypothesis testing are stressed first to pave the way for understanding experimental design concepts.  The course explains in detail various designs that help the investigator to plan and carry out experiments efficiently.  The experimental designs may be also used for eventual process optimization.  Emphasis is placed on interpretation of the results from the Analysis of Variance (ANOVA) and analysis of residuals.  Fitting of empirical models using linear regression techniques will also be explained.

Learning outcomes:

Students will

  1. familiarize with basic concepts such as random errors, random variables, random sampling and hypothesis testing
  2. distinguish between determinate and indeterminate errors and quantify them
  3. compare variability due to random errors with variability from controlled process factors
  4. choose appropriate design of experiments
  5. estimate pure error in the experiments
  6. interpret ANOVA results and identify significant factors that influence the experiments
  7. fit empirical models to experimental data using linear regression concepts
  8. optimize processes using response surface methodology

Course Contents:

  1. Overview of the subject
  2. Determinate and indeterminate errors and their analyses
  3. Presentation of experimental data
  4. Random variables and continuous probability density functions
  5. Standard probability distribution functions: Normal, Student’s T, chi-square and F distributions
  6. Hypothesis Testing and confidence intervals
  7. Experimentation involving one variable
  8. Analysis of Variance (ANOVA) concepts
  9. Factorial Design of Experiments
  10. Orthogonal experimental designs
  11. Central composite and Box-Behnken designs
  12. Response surface methodology
  13. Multi-variable linear regression
  14. Advanced experimental design concepts

Text Books

  1. Montgomery, D. C., G.C. Runger, Applied Statistics and Probability for Engineers. 5th ed. New Delhi: Wiley-India, 2011.
  2. Montgomery, D. C., Design and Analysis of Experiments. 8th ed. New Delhi: Wiley-India, 2011.

 Reference Books:

  1. Myers, R. H., D. C. Montgomery and C. M. Anderson-Cook, Response Surface Methodology. 3rd ed. New Jersey: Wiley, 2009.
  2. Ogunnaike, B. A., Random Phenomena. Florida: CRC Press, 2010