  Orthogonal Arrays allow us to test various levels of each factor and balance
the different factors so that we can estimate interactions as well as first
order effects. There is a trade-off between how well we can sample different
levels of each factor and how many interactions we are able to estimate. This
paper describes one method to mitigate this trade-off. This method will allow
us, with n observations, to sample n levels of each factor and minimize the
correlation between the estimates of first order terms and their interactions.
