It is a wide category of variable which is infinite and has no numerical data. These variables are called as qualitative variables or attribute variable in terms of statistics software. Such variables are further divided into nominal variables, ordinal and dichotomous variables. Nominal variables don’t have any intrinsic order. For instance, a developer classifies his environment into different types of networks based on their structure, such as P2P, cloud computing, pervasive computing, IoT. So here, the type of network is a nominal variable comprised of four categories. The varied categories present in the nominal variable can be known as the nominal variable levels or groups.Dichotomous variables are also called binary values, which have only two categories.
For example, if we question a person that he owns a car, he would reply only with yes or no. such types of two distinct variables that are nominal are called as dichotomous. It just accounts for only two values, such as 0 or 1. It could be yes or no, short or long, etc.Ordinal variables are nominal variables that include two or multiple categories. If you see any hotel feedback form, it has five ratings such as excellent, good, better, poor and very poor. So we can rank the level with the help of ordinal variables that hold meaning to the research. It is unambiguous, and values can be considered for decision making.