In Design of Experiments, blocking involves recognizing uncontrolled factors and ensuring as wide a spread across these factors.
Confounding occurs when you can’t distinguish the effects of certain factor interactions because of other potential factor effects.
Yates analysis is a method of analyzing data from full and partial factorial design experiments. It requires two levels for each factor in the experiment.
Factorial Design Overview covers one of the key issues in designing an experiment: identifying as many influences on the results as possible.
In most experiments, you’ll have a number of factors to deal with. These are elements that affect the outcomes of your experiment. They fall into a few basic categories: