Statistics deals with the study of gathering, observing, calculating, and interpreting the numerical data. It is full of experiments and research. A statistical experiment is defined as an ordered procedure which is performed with the objective of verifying, determining the validity of the hypothesis. Before performing any experiment, some specific questions for which the experiment is intended should be clearly identified. To minimise the variability effect on the result of interest, the experiment has to be designed. So, the researcher will design the experiments for the purpose of improvement of precision. It is called experimental designs or the design of experiments(DOE). In this article, let us discuss the definition and example of experimental design in detail.
Experimental Design Definition
In Statistics, the experimental design or the design of experiment (DOE) is defined as the design of an information-gathering experiment in which a variation is present or not, and it should be performed under the full control of the researcher. This term is generally used for controlled experiments. These experiments minimise the effects of the variable to increase the reliability of results. In this design, the process of an experimental unit may include a group of people, plants, animals, etc.
Application of Experimental Design
The concept of experimental design is applied to Engineering, Natural Science and Social Science as well. The areas in which the experimental designs used are:
- Evaluation of physical structures, materials and components
- Chemical formulations
- Computer programs
- Opinion polls
- Natural experiments
- Statistical surveys
A quasi-experimental design is similar to the true experimental design, but there is a difference between the two.
In true experiment design, the participants of the group are randomly assigned. So, every unit has an equal chance of getting into the experimental group.
In a quasi-experimental design, the participants of the groups are not randomly assigned. So, the researcher cannot make a cause or effect conclusion. Thus, it is not possible to assign the participants into the group.
Randomized Block Design
The randomised block design is preferred in the case when the researcher is clear about the distinct difference among the group of objects. In this design, the experimental units are classified into subgroups of similar categories. Those groups are randomly assigned to the group of treatment. The blocks are classified in such a way in which the variability within each block should be less than the variability among the blocks. This block design is quite efficient as it reduces the variability and produces a better estimation.
In a drug testing experiment, the researcher believes that age is the most significant factor. So he divides the units according to the age groups such as
- Under 15 years old
- 15 – 35 years old
- 36 – 55 years old
- Over 55 years old
Completely Randomized Design
Of all the types, the simplest type of experimental design is the completely randomized design, in which the participants are randomly assigned to the treatment groups. The main advantage of using this method is that it avoids bias and controls the role of chance. This method provides a solid foundation for the Statistical analysis as it allows the use of probability theory.
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