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Types of Variables
Variables can be of different types and, sometimes, different software uses different names for the same variables. So, let's get familiar with the different kinds of variables that we will work with:
- Continuous: A continuous variable can take an infinite number of values, such as time or weight. They are of the numerical type.
- Discrete: A variable whose values are whole numbers (counts) is called a discrete variable. For example, the number of items bought by a customer in a supermarket is discrete.
- Categorical: The values of a categorical variable are selected from a small group of categories. Examples include gender (male or female) and make of car (Mazda, Hyundai, Toyota, and so on). Categorical variables can be further categorized into ordinal and nominal variables, as follows:
- Ordinal categorical variable: A categorical variable whose categories can be meaningfully ordered is called ordinal. For example, credit grades (AA, A, B, C, D, and E) are ordinal.
- Nominal categorical variable: It does not matter which way the categories are ordered in tabular or graphical displays of the data; all orderings are equally meaningful. An example would be different kinds of fruit (bananas, oranges, apples, and so on).
- Logical: A logical variable can only take two values (T/F).
You can read more about variables at http://www.abs.gov.au/websitedbs/a3121120.nsf/home/statistical+language+-+what+are+variables.
The following table lists variables and the names that R uses for them; make sure to familiarize yourself with both nomenclatures.
The variable names used in R are as follows:
In R, whenever the factor data is listed, the number of levels is also given. A dataset can contain different kinds of variables, as discussed previously.