Design of Experiments Fundamentals

Design of Experiments (DOE) is a procedure to planning, designing and analysing experiments to effectively and efficiently draw valid and statistically sound conclusions.

This course aims to:

• Familiarise delegates with DOE principles and terminology (randomisation, replication, blocking, factors, effects, interactions, ANOVA, hypothesis testing)
• Provide statistical background theory in order to understand DOE process and development
• Demonstrate the steps of a full factorial experiment design in order to optimise response to key factors
• Analysis of results using hypothesis test plots and regression modelling
• Explain the purpose of non full factorial designs

By the end of the course, delegates should be able to:

• Define key terminology (factors, effects, interactions, anova, hypothesis testing)
• Explain key principles (randomisation, replication, blocking,)
• Calculate Coefficients of a simple linear regression model
• Describe the steps in designing a full factorial experiment
• Create a coded 3 factor 2 level full factorial design matrix
• Perform a hypothesis test
• Perform an analysis of variance
• Interpret common DOE plots (interaction effects, cube plots, Normal Probability Plots, Contour Plots, Pareto Charts, Optimal Solutions)
• Justify the choice of experiment design approaches

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