What is the design of experiments?
Advances in the field of technology and scientific knowledge are often caused by profits in using a suitable design of experiments. Understanding this statistical concept allows scientists to assign the relationships of causes and effects and remove the conjecture and prejudices from the analysis of the results. Business and economic issues require as much care as scientific research in designing experiments.
In the scientific proposal of experiments, the researcher attempts to demonstrate a logical statement: if X, then Y. On the contrary, it must also be proven to create the relationship of the cause and consequence: if not x, then not Y. intuitively, for example, that the plant needs to live. Thus, there is a causal relationship between the needs and water of the plant.
The researcher attempts to demonstrate both logical statements using the use of a power control group. Ideally, the same research entities experience the same experimental conditiony simultaneously. If this is not possible, as is often the case in biological experiments, the second group of entities is associated with the first group in as many factors as possible, how much can the results can affect. For example, the effectiveness of the diet can be tested by selecting a control group similar to a test group at age, income, activity level and number of children. In critical experiments, the design of experiments will include actual comparison of individual entities; This means that subject number 1a will be the same age, gender, activity level and initial weight as subject number 1b but receive a test diet while 1a will not.
Factorial proposals allow to study more than one variable in the same experiment, but with the same rigor as control groups, using probability mathematics. The breakthroughs in the genetics reached by Mendel were DUE for factorial experiments and observations. In these experiments, two or more independent factors are tested at two or more levels. For example, subjects may beT divided between three independent variables: regular diet, diet or diet B. Each of these subgroups is again divided based on how long the diet is used, either three weeks or six weeks.
statistical methods are relatively easy to apply to the design of experiments in the realm of natural sciences. In social sciences that include behavioral studies, they are more difficult. In the Economics and Business Study, there are objects of people and societies. These entities are not easy to study at all.
Marketing studies often depend on focus groups whose care is critical in the selection. Knowledge of the correct proposal of experiments is necessary to determine the selection criteria. Surveys, a common tool of product managers and political groups, also require this expertise in their design.