Sorting it out: A Guide to Ordinal and

Nominal Data

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Data, data, everywhere! Numbers dance across spreadsheets, charts bursting with colorful bars...but not all data is created equal. Ordinal and nominal, ever heard of them?

Imagine a movie theatre:

The seat numbers tell you where to sit, but there is no inherent order or comparison between them. You would not claim that one seat is better than the other. This is basically nominal data.
Picture the rows: front row, middle row! The front row sits closer to the screen, the back row farther, and the middle row falls somewhere in between. Each level has a definite rank compared to the others. This is ordinal data.

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OK what is the difference?

Nominal data:

Think categories, not ranks. Imagine hair color, political party, or music genre. These are nominal-just labels that group things together without implying any order or inherent relationship.
Surveys and questionnaires love them. Ask "What is your favorite color? and you will get nominal data like blue, green, and purple without inherent order just individual categories.
Counting and percentages are their forte. We can count how many people like each color, but we cannot say blue is greater than green.

Ordinal data

Ranks matter! Think movie rows, exam grades, or clothing sizes. These levels have a clear order, each higher than the one below.
They tell you more than or less than. A student with an A outperformed someone with a C. A large shirt is bigger than a medium.
But beware of stretching the order!! Ordinal data does not always allow for equal intervals between levels. A B student is not necessarily twice as good as a D student.

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Why does it matter??

Choosing the right data type is crucial for accurate analysis and meaningful conclusions. Using nominal data for calculations that assume order can lead to misleading results. Conversely, forcing ordinal data into strict mathematical operations might not make sense.

Data is like legos: different pieces fit together in different ways. Knowing which type you're holding is key to building something insightful and robust.

So, next time you see data dancing around, do not be afraid to ask: ordinal or nominal to unlock a hidden story within the numbers.

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There are other data types out there, like interval and ratio data, each with their own quirks and strengths.