Numerical variables can be divided into the following two categories:
Discrete variable: the value can only be calculated in natural number or integer unit, and its value is discontinuous, and there is no other value between two adjacent values. The value of this variable is generally obtained by counting.
Continuous variable: you can take any value in a certain interval, and its value is continuous. Two adjacent values can be divided infinitely, that is, they can take infinite values. Such as height, length of rope and so on.
Compared with discrete variables, continuous variables have the concept of true zero, so they can be multiplied and divided.
Classification variables can be divided into the following two categories:
Ordered variable: describes the rank or order of things. The variable value can be numeric or character, which can further compare the advantages and disadvantages, such as the degree of liking: like it very much, like it generally, and dislike it.
Nominal: there is no order difference between values, only classification, which can be divided into binary and multi-classification variables? Dichotomy variable refers to dividing all data into two categories, such as male and female, right and wrong, yin and yang, etc. Dichotomy variable is a special classified variable with its unique analysis method. ? Multi-classification variables refer to more than two categories, such as blood types divided into A, B, AB and O.
The difference between ordered classified variables and unclassified variables is that the former is meaningful for comparison operation, while the latter is meaningless for comparison operation.