The number is just a label or a name of a category and does not on its own have any genuine mathematical properties.
Nominal data counts the number of times something has occured in a given category (e.g number of males or females in a class, number of students that have acheived and A or U grade etc)
Because this data can only work out the proportion of something, it is not possible to analyse it by working out central tendencies (mean,median and mode) and is best displayed using a pie-chart.
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Ordinal Data
This type of data involves numbers that can be put in order or ranked but do not have any other mathematical properties.
Any data that creates a score can be treated as ordinal especially data collected from self-reports, questionnaires, preference rating scales or observations
This type of data can be analysed by working out the central tendencies and measures of dispersion, which can be displayed in a bar-chart
However, it cannot tell us about the differences between scores that might vary.
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Interval and Ratio Data
This is the most complex type of data as it allows us to understand the differences between scores rather than just the relationship between them
For data to be classed as interval the points on a given scale must be equally spaced, which means that the data is measured in equal units (e.g temperature or IQ test)
Interval Data involves both positive and negative values
Ratio Data has an absolute zero which makes it the most precise type of measurement.
In general, this level of data tends to be referred to as "at least interval level"
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