What Is Data?
Every day, we are surrounded by information — the temperature outside, the colours of cars in a car park, the number of goals scored in a football match. In mathematics and science, we call this collected information data.
Facts and information collected for analysis. Data can be numbers, words, measurements, or observations about the world.
In statistics, the things we measure or observe are called variables — because their values can vary (change) from person to person or object to object.
A variable like plant height can take different numerical values (e.g. 12 cm, 45 cm, 3 cm).
A variable like flower colour can take different category values (e.g. red, yellow, white).
Before we can spot patterns or draw conclusions, we need to understand what type of data we are dealing with. Different types of data are collected, organised, and displayed in different ways.
Raw Data
When data is first collected — before it has been sorted, organised, or summarised — it is called raw data.
Data in its original, unorganised form, exactly as it was collected. It has not yet been sorted, grouped, or processed.
Raw data often looks like a messy list of numbers or words. For example, here are raw data from a survey of the number of rubbish bags put out per household on collection day:
3, 2, 2, 3, 1, 2, 1, 1, 3, 1, 2, 1, 2, 0, 2, 3, 3, 4, 4, 6
This information is valuable, but in its raw state it is hard to read or interpret. To find patterns, we need to organise it — for example, by sorting the numbers in order or putting them into a frequency table.
Think of raw data like a pile of LEGO bricks tipped straight out of the box onto the floor. All the pieces you need are there, but until you sort and organise them, it is very difficult to build anything useful!
Organising data — numerically, by category, or by converting tallies into totals — makes it much easier to work with and draw conclusions from.
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