Avoiding lurking variables
The varying characteristics of the experimental units can only be lurking variables if they are associated with the allocation of treatments to the experimental units. A completely randomised design for the experiment minimises the possible association with lurking variables.
Effect of a packer on speed of checkout operators
With randomisation, there is no tendency to over- or under-estimate the effect of the packer.
Mechanics of randomisation
There are several different ways to randomise allocation of treatments to the experimental units. These all use random numbers either from printed tables or, preferably, generated by a computer. The simplest method is to use a spreadsheet such as Microsoft Excel.
Randomisation of treatments in Excel
Other ways to randomise treatments (optional)
Although the above method of randomly allocating treatments to the experimental units using a spreadsheet is recommended, two alternative methods are now described. The first illustrates the randomisation better, whereas the second provides an interesting application of probability.
Random allocation of sales staff to training courses
This method can be rather slow since many random indices are rejected towards the end of the method because treatments have already been allocated to these experimental units.
Random allocation of sales staff to training courses
The final randomisation method works through all experimental units in order, picking a random treatment for each unit in turn. The only complication is that the probabilities used to generate the treatments must be adjusted after each unit gets a treatment. For example, if the first unit gets treatment A, then the probability of the second unit getting treatment A must be reduced a little. (If the same probabilities were used for each successive unit, then too many treatment A's might be allocated.)