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In statistics, a variable is a characteristic or attribute that can take different values. It can be classified into different types based on its nature and how it is measured. The two main types of variables are categorical variables and numerical variables. Categorical variables, also known as qualitative variables, represent categories or groups. They can be further divided into nominal variables and ordinal variables. Nominal variables have categories that do not have a natural order or ranking, such as gender or eye color. On the other hand, ordinal variables have categories that can be ranked or ordered, such as a Likert scale response or a rating of satisfaction. Numerical variables, also known as quantitative variables, represent quantities or measurements. They can be further divided into discrete variables and continuous variables. Discrete variables have a finite or countable number of possible values, such as the number of siblings a person has or the number of cars in a parking lot. Continuous variables, on the other hand, can take any value within a certain range, such as height or weight. Variables play a crucial role in statistical analysis as they help in describing, organizing, and summarizing data. They are used to identify patterns, relationships, and differences between groups, and are often used as inputs in statistical tests and models.
