In a nutshell

Data can be classified in lots of different ways: discrete or continuous, primary or secondary, qualitative or quantitative. You can also organise data into groups known as classes to make it more organised.

Different kinds of data

Data can be split into a number of different categories, all of which can be useful depending on the situation.

Definitions and examples

Discrete	Whole number data that is counted, not measured	The number of customers at a food stall
Continuous	Measurable data that could take any value in a range	The heights of students in a class: $155cm, 155.2cm, 145.7cm$
Qualitative	Describes things using words, not numbers	Asking how people are feeling: happy, sad, angry
Quantitative	Measures quantities using amounts	Number of days until a person's birthday
Primary	Data that you have collected yourself	Going around the class and finding everyone's shoe size
Secondary	Data that someone else has collected	Data about UK rivers found on a website

Organising data into classes

To record data in a table, you may need to organise it into classes to make it more manageable. The data classes must not overlap and every part of the data should be covered by a class. For discrete data, these classes should have gaps in between, like you see below. For continuous data, these classes should be written as inequalities.

Example

Mike is collecting data about the ages of teachers in his school. He groups the data in the following way:

Age	Frequency
$21-25$	$7$
$26-35$	$22$
$36-45$	$13$
$46-55$	$18$
$56-65$	$17$
$66$ and over	$2$