Components of an Experiment/ Terminology Experimental Design (I)
When you design an experiment you have a question to answer. For example, that some property of say some genotypes (eg grain yield, plant height, resistance level, etc.) depends on other properties or quantities of those genotypes or the properties of some external condition. Each experiment consist of:
A response variable: the property of prime interest that is measured and that you want to study (e.g. grain yield, plant height, etc).
One or more explanatory variables: the property or properties that you think will affect the response variable and that you want to investigate. There are two major types of explanatory variables:
Factor: categorical explanatory variable classifying each observation as belonging to a specific group. Each group of a factor is called a factor level. A distinction can be made between:
- Treatment factors: factors with levels that are of direct interest and that we want to compare, for example Variety with levels variety A, B, and C.
- Blocking factors: factors with levels that are not of direct interest, but that are important to control variation in the experiment, so are part of the experimental design, for example blocks.
Covariate: is a continuous explanatory variable that quantifies some property of each observation on a continuous scale. Again, we can make the distinction between covariates that are of interest (for example the amount of nitrogen in kg/ha when you want to investigate the effect of nitrogen on say, grain yield) or covariates that are used to correct for differences between experimental units that are not related to the treatments (reduces the experimental error).