In this article I will be describing the difference between quantitative variables and qualitative variables. In statistics, the classification of variables depends on whether or not they can be written down as a number.
In general, observations and measurements can be regarded as variables, and these variables are known as data.
Quantitative Variables
Variables that are associated with numerical observations are called quantitative variables.
*Example: The observations of height are numerical as you can give a number to them. This means that height is a quantitative variable. Another example could be the weight of a smartphone.
Qualitative Variables
Variables that are associated with non-numerical observations are called qualitative variables.
*Example: The colour of a t-shirt is not numerical, therefore it's a qualitative variable.
More about quantitative variables:
Quantitative variables can be measured on either continuous or discrete scales.
A variable that can take up any value within a given range is called a continuous variable. [Examples: Time, length and weight]
A variable that is restricted to taking up only specific values within a given range is called a discrete variable. [Examples: Number of £1 coins in a bag, number of boys in a family]
So, the next time you're making an observation, question whether that observation is quantitative or qualitative. And if it's quantitative - is the measurement you're making continuous or discrete?
In real life there are many examples of quantitative and qualitative variables. All it takes is a little practice and attention to start categorising your data correctly.
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