There are multiple approaches for determining the set of design points (unique combinations of the settings of the independent variables) to be used in the experiment. Experimental design involves not only the selection of suitable independent, dependent, and control variables, but planning the delivery of the experiment under statistically optimal conditions given the constraints of available resources. In its simplest form, an experiment aims at predicting the outcome by introducing a change of the preconditions, which is represented by one or more independent variables, also referred to as 'input variables' or 'predictor variables.' The change in one or more independent variables is generally hypothesized to result in a change in one or more dependent variables, also referred to as 'output variables' or 'response variables.' The experimental design may also identify control variables that must be held constant to prevent external factors from affecting the results. The term is generally associated with experiments in which the design introduces conditions that directly affect the variation, but may also refer to the design of quasi-experiments, in which natural conditions that influence the variation are selected for observation. The design of experiments ( DOE or DOX), also known as experiment design or experimental design, is the design of any task that aims to describe and explain the variation of information under conditions that are hypothesized to reflect the variation. Design of experiments with full factorial design (left), response surface with second-degree polynomial (right)

What is the meaning of doe