When running a statistical analysis, it is very likely that you will stumble across terms like ‘ordinal variable’ or ‘nominal variable’. While many of us have a basic idea of what the different types of variables are, the nomenclature can get confusing.
Before embarking on your research journey, selecting your statistical tools and collecting your data, let’s take a quick look at the different types of variables you may encounter. When using different statistical analyses software such as SPSS, you will see these words and when you have a grasp of them makes the learning process much smoother.

Constant:
While this is not a variable, it is still important to understand the difference between a constant and a variable. A constant, to explain it simply, is a measure whose value remains constant. For example, the number of days in a week is constant. 
Variable:
In contrast, a measure whose value is not fixed is known as a variable. Age, gender, height and weight are all common examples of variables. The three main types of variables that will be discussed here include categorical, ordinal and interval variables. To better understand these terms, let us refer to the hypothetical example below.
Example:
A 5thgrade classroom consists of 10 students. As part of a math class on statistical data collection and frequency analyses, the classroom teacher records the students’ gender, heights and marks in mathematics. The information is as shown below.
S. No.  Gender  Height  Marks 
1.  Male  Tall  7080 
2.  Male  Tall  8090 
3.  Female  Medium  7080 
4.  Male  Tall  90100 
5.  Female  Short  90100 
6.  Female  Tall  7080 
7.  Male  Medium  7080 
8.  Female  Tall  7080 
9.  Female  Tall  8090 
10.  Male  Medium  8090 
In this example, gender is a categorical variable. Categorical variables or nominal variables are those possessing more than one category, but no specific order. For instance, gender, in this case, exists as two groups of either male or female, but there is no arbitrary order for the use of these groupings.
Similar to a categorical variable is an ordinal variable, in this example represented by height. Ordinal variables are in which the categories have some specific order. We know that the order to be considered here is short, medium and tall and it can be assumed that the teacher has defined each category by some fixed constants.
The last type of variable is an interval variable, which is similar to an ordinal variable except that the intervals are equal. The last column lists the students’ marks in mathematics, grouped according to intervals of 10. We can order the categories according to their numerical value and the interval between each category is equal.
Are there any other types of variables you should know about?
When working with statistical software and tools, you may come across the terms ‘independent’ and ‘dependent’ variables.
An example of this is if we are examining a collection of data about the change in consumption of chocolate according to age.
In this case, age is the independent variable, it does not depend on anything. The change in chocolate consumption becomes the dependent variable as it depends on age.
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