Mixture formation plays
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insufficient, the use of methods of experimental design lets you upgrade mathematical model of conducting additional experiments without loss of prior information and cost.

The purpose of planning the experiment – of these terms and conditions of the experiments in which is possible to obtain reliable and accurate information about the object with the least expenditure of labor, and present this information in a compact and convenient form of quantitative assessment of accuracy.

Let studied property of an object depends on Y n independent variables (Х1, Х2, ..., Хn) and we want to clarify the nature of this relationship – Y =

F (Х1Х2, ..., Хn), which we have only a general idea. The value of Y – called "review", and the dependence Y = F (Х1, Х2, ..., Хn) – "response function".

Feedback should be quantified. However, there may be signs of quality and Y. In this case, the possible use of rank approach. Example rank approach – score on the exam when one number is estimated complex combination obtained information about the student's knowledge.

Independent variables Х1, Х2, ..., Хn – other factors also need to have a quantitative assessment. If there are qualitative factors, then each of their level must be assigned a certain number. It is important to choose only factors as independent variables, ie only those that can be changed without affecting other factors. Factors to be mixed. Moves to a mathematical model to hold the preliminary analysis of the significance of factors (degree of influence on the function), their ranking and exclude minor factors.

The range of changes in factors set domain of Y. If we assume that each factor corresponds coordinate axis, then the resulting space is called the factor space. When n = 2 domain of Y is a rectangle, for n = 3 – cube, for n> 3 – hypercube. When choosing a range of factors to take into account changes compatible, ie control to any of these bands – that combination of factors would be