This course covers the fundamentals of the design and analysis of experiments (DoE). Using these principles, you will learn to critically analyze experimental data and gain valid, objective conclusions. We will cover basic statistics concepts to understand the fundamentals of hypothesis testing and analysis of variance. Then we move onto factorial designs, with the definition of effects and interactions between factors. The course is illustrated with practical examples. We will use R and MS Excel for the analysis of the data.

What You Will Learn

– A Brief History of Experimental Design
– The One Factor At a Time (OFAT) Approach and its limitations
– The Three Pillars of DOE: Replication, Randomization and Blocking
– Factorial Experimentation: basic concepts
– Fractional Factorials: getting more with less
– Resolution of designs
– Brief Overview of Screening and Response Surfaces
– A/B Testing