What is a split-plot analysis?
The split-plot design is an experimental design that is used when a factorial treatment structure has two levels of experimental units. The whole plot is split into subplots, and the second level of randomization is used to assign the subplot experimental units to levels of treatment factor B.
What is split-plot design in research?
A split-plot design is an experimental design in which the levels of one or more experimental factors are held constant for a batch of several consecutive experimental runs, which is called a whole plot. A split-plot design results in correlated responses for the experimental runs in the same whole plot.
What makes a split plot design different than a factorial design with blocking?
The split-plot design in this example has only one whole-plot factor and one subplot factor. The key difference between split-plot designs and randomized block designs is that, in randomized block designs, the factor level combinations are randomly assigned to the experimental units in the blocks.
When would you use a split plot design?
A split plot design is a special case of a factorial treatment structure. It is used when some factors are harder (or more expensive) to vary than others. Basically a split plot design consists of two experiments with different experimental units of different “size”.
Why we use split-split plot design?
The split-split plot arrangement is especially suited for three or more factor experiments where different levels of precision are required for the factors evaluated.
How do you calculate factorial design?
The number of different treatment groups that we have in any factorial design can easily be determined by multiplying through the number notation. For instance, in our example we have 2 x 2 = 4 groups. In our notational example, we would need 3 x 4 = 12 groups. We can also depict a factorial design in design notation.
When do you use a split plot design?
A split plot design is a special case of a factorial treatment structure. It is used when some factors are harder (or more expensive) to vary than others. Basically a split plot design consists of two experiments with different experimental units of different “size”.
What makes a split plot an experimental error?
(If you recall, we mentioned that any interaction between the Blocks and the treatment factor is considered part of the experimental error). Similarly, in the split-plot section of the analysis of variance, all the interactions which include the Block term are pooled to form the error term of the split-plot section.
Who was the inventor of the split plot?
Split-Plot experiments were invented by Fisher (1925) and their importance in industrial experimentation has been long recog- nized (Yates (1936)). It is also well known that many industrial experiments are fielded as split-plot exper- iments and yet erroneously analyzed as if they were completely randomized designs.
Why are whole plots divided into three parts?
As we can see, in order to achieve this economy in the process, there is a restriction on the randomization of the experimental runs. In this example, each replicate or block is divided into three parts called whole plots (Each preparation method is assigned to a whole plot).