Categorical vs Quantitative Data
Although both categorical and quantitative data are used for various researches, there exists a clear difference between these two types of data. Let us comprehend this in a much more descriptive manner. In statistics, observations are recorded and analyzed using variables. The variables are categorized into classes by the attributes they are used to measure. Categorical and Quantitative are the two types of attributes measured by the statistical variables. Through this article let us examine the differences between categorical and quantitative data.
What are Categorical data?
Qualitative variables measure attributes that can be given only as a property of the variables. The political affiliation of a person, nationality of a person, the favorite color of a person, and the blood group of a patient can only be measured using qualitative attributes of each variable. Often these variables have limited number of possibilities and assume only one of the possible outcomes; i.e. the value is one of the given categories. Therefore, these are commonly known as categorical variables. These possible values can be numbers, letters, names, or any symbol.
What are Quantitative data?
Quantitative variable records the attributes that can be measured by a magnitude or size; i.e., quantifiable. Variables measuring temperature, weight, mass or the height of a person or the annual income of a household are quantitative variables. Not only all the values of these variables are numbers, but each number gives a sense of value too.
The data in quantitative type belong to either one of the three following types; Ordinal, Interval, and Ratio. Categorical data always belong to the nominal type. Above mentioned types are formally known as levels of measurement, and closely related to the way the measurements are made and the scale of each measurement.
Since the form of the data in the two categories is different, different techniques and methods are employed when gathering, analyzing, and describing.
What is the Difference Between Categorical and Quantitative data?
Definitions of Categorical and Quantitative data:
- Quantitative data are information that has a sensible meaning when referring to its magnitude.
- Categorical data are often information that takes values from a given set of categories or groups.
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:
- 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.
Analysis:
- 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.
Image Courtesy:
1.”ECE weekly 235” by UNECE – ECE Weekly. [GFDL] via Wikimedia Commons
2.”History of Bank Rate” by Anu2033 – Own work. [CC BY-SA 3.0] via Wikimedia Commons
