Distinguish between a quantitative and a categorical variable.

October 30, 2019

Categorical variables
Categorical variables are also called qualitative variables or attribute variables. The values of a categorical variable are mutually exclusive categories or groups. Categorical data may or may not have some logical order.
Quantitative variables values of a quantitative variable are numbers that usually represent a count or a measurement.
Often, you will collect both categorical data and quantitative data when exploring a single subject. Categorical variables are often used to group or subset the data in graphs or analyses. Here are some examples of categorical and quantitative data that you could collect when exploring the same subject:
Subject of the analysisPossible categorical variablesPossible quantitative variables
Household appliance sales
Type of appliance; Make and model
Sale price
Automobile body painting
Paint flaws (peel, scratch, smudge, other); Paint colors
The temperature of the metal to be painted; Thickness of the paint layer

Quantitative variables

Quantitative variables are measured and expressed numerically, have numeric meaning, and can be used in calculations. (That’s why another name for them is numerical variables.) Although zip codes are written in numbers, the numbers are simply convenient labels and don’t have numeric meaning.

Categorical variables

A categorical variable doesn’t have numerical or quantitative meaning but simply describes a quality or characteristic of something.
The numbers used in categorical or qualitative data designate a quality rather than measurement or quantity. 

Characteristics of Categorical and Quantitative data:

 Class of measurement:
  • Quantitative data belong to ordinal, interval, or ratio classes of measurements.
  • Categorical data belong to the nominal class of measurements.
  • Methods used to analyze quantitative data are different from the methods used for categorical data, even if the principles are the same, at least the application have significant differences.
  • Quantitative data are analyzed using statistical methods in descriptive statistics, regression, time series, and many more.
  • For categorical data, usually descriptive methods and graphical methods are employed. Some non-parametric tests are also used.
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