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Attributes are detected by their presence or absence in a particular individual. Statistics is therefore widely used to determine attributes through the various numbers of techniques available. These statistical methods are used in the study of variables and are used in a wide scope in the theory of attribute. The theory of attribute has certain representations. A population is divided into two classes (i.e. negative and positive). This is done in accordance to the presence or the absence of attribute. The positive class indicating the absence of the attribute is represented by the roman letters A, B, C etc., while the negative class is indicated by Greek letters - α, β etc.
Any combination between two attributes is denoted by assembling the two attributes. For example, if the combination is A and B, then the letters would be denoted as AB. If the population is divided into two subclasses, then it is called dichotomous classification. Observations that have been allocated to the attributes are termed as class frequencies, which are denoted by bracketing the attribute symbols. For instance, (A) stands for the frequency of the attribute A. A class characterized by ‘n’ attribute is called a class of nth order and the matching frequency of that attribute is the frequency of the nth order. An example, (A) is a class frequency of the first order. These class symbols of the attribute also work as an operator. For example, A.N=(A) implies that the process of dichotomizing N in accordance to the attribute A gives the class frequency equal to (A). Attributes A and B are said to be independent only if there is no connection between the two. When independent, the same proportion of A attribute occurs amongst B attribute and amongst the β attribute, and the proportion of B attribute amongst A attribute is same as that amongst the α attribute. The attributes A and B may be considered to be linked if they are not independent but are related in some way. For positive association between two attributes, (AB) > (A) (B) / N and are negatively connected if (AB) < (A) (B) / N. If attribute A cannot occur with attribute B, but attribute B can occur with attribute, A (or vice versa), then the two attributes are actually connected. Again, two attributes are said to be connected if the two occur together in a number of cases. The reliability between the two attributes (A)=20 and (AB)=25 is not present as the attribute (AB) cannot be greater than the attribute (A) if they have been studied from the same population.
The consistency between the two attributes (A)=20 and (AB)=25 is not present as the attribute (AB) cannot be greater than the attribute (A) if they have been observed from the same population.
