Decision tree testing (DTT) is a methodology used by researchers in various fields to speculate on or anticipate the results of decisions. As its name suggests, the ensuing diagram resembles a tree or its branch systems. Depending on the cause or content of the study, the features of those units can be different.
In the tree design, each starting point represents a potential decision and branches stemming from it illustrate different options available. In some cases, researchers determine if the relative outcomes of each possible decision are unavoidable and assign levels of desirability or undesirability to those outcomes. If they are uncertain, whole new branch systems are incorporated to show variables. Often, decision trees begin with two-fold or binary decision possibilities that may be expanded.
Decision trees are frequently seen in business and especially scientific environments of study and forecasting. With regard to science, these tree tests are used to evaluate everything from genetics to social phenomena, such as drug and alcohol use. They can even be used by companies to develop testing procedures for the likelihood of controlled substance use among employees.