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I N F O G R A P H I C B Y I N T E L L S P O T . C O M
CategoricalData
Definition, characteristics,examples
Categorical data is data that is divided into groups or
categories. These categories are based on qualitative
characteristics such as gender and colors or something
else that doesn’t have a number associated with it.
This doesn’t mean that categorical data cannot
have numerical values.
In fact, categorical data often takes numerical
values, but those numbers don’t have any
mathematical meaning. They just represent the
number of items in each group. For example 12
blondes in a class.
D E F I N I T I O N
KEY CHARACTERISTICS OF CATEGORICAL DATA
Categorical data is
divided into groups or
categories.
The categories are
based on qualitative
characteristics.
There is no order to
categorical values and
variables.
Categorical data can take
numerical values, but those
numbers don’t have any
mathematical meaning.
Categorical data is
displayed graphically by
bar charts and pie
charts.
1
EXAMPLES OF CATEGORICAL DATA:
Gender (Male,Female)
2
Hair color (Blonde, Brunette, Brown, Red, etc.)3
Brand of soaps(Dove, Olay…)
4
5
6
Survey on a topic “Do you havechildren?” (Yes or No)
Motives for traveling (Leisure, Business Travel,To Visit Friends and etc.)
Age group (under 12 years old, 12-17 years old, 18-24 yearsold, 25-34 years old, 35-44 years old and etc.)
C A T E G O R I C A L A N D Q U A N T I T A T I V E D A T A : D I F F E R E N C E
Quantitative data is
measured and expressed
numerically. It is used in
calculations and arithmetic.
In comparison, the
categorical data does not
have any numerical
meaning.
Examples of quantitative
data: weight, temperature,
GPA, annual income,
number of hours spent
working. Types of
quantitative data are:
ordinal, interval, and ratio.
Categorical data is only
one type – the nominal
type.
Quantitative data are
analyzed using descriptive
statistics, time series, linear
regression models, and
much more. For categorical
data, typically only
graphical and descriptive
methods are used.
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