Experimental designs should be categorized with many a variations. They can be classified and organised by understanding the application of the fundamental signal to noise ratio metaphor. This metaphor elucidates that what we see or observe can be split into two basic components. These two components are the signal and the noise.
In most of the researches, the signal has its link with the key variable of interest. The noise here comprises the random factors in the situation which make the visibility of the signal in the room relatively poorer. A ratio construct can be created when the signal is divided by the noise. When one talks of research, the signal should have high relativity to noise. For instance, if the treatment or programme and the measurement is also very good they can be termed as strong signal and low noise. In light of this concept, the experimental designs can also be classified into two categories. They can be termed as signal enhancers or noise reducers. Both these categories work towards enhancing the quality of the research. The first kind which is the signal enhancing experimental design is technically called the factorial designs. In this type of design, the entire focus is on the set up of the programme. It would help to examine and understand the different variations of a treatment.
In the other category, there are two major types of noise reducing experimental designs. They are called the covariance designs and blocking designs. The basic purpose of this kind of a design is to put the sample information and pre programme variables so that some noise from the study is taken out and more precise and worthy analysis can be done
