Welcome to Really Simple Statistics (RSS). There are lots of places online where you can ponder over the minute details of complicated equations but very few places that make statistics understandable to everyone. I won’t explain exceptions to the rule or special cases here. Let’s just get comfortable with the fundamentals.
Today we tackle another kind of number. Unlike nominal numbers, ordinal numbers have real meaning behind them. The name itself hints at the meaning. Ordinal numbers portray ordered numbers.
But, the only thing we know about the numbers is that there is an order to them. For example, there are more cookies in the first picture than there are in the second. But, we can’t see the whole picture, so we don’t know how many more cookies are in the first picture. We could assign a a 2 to the first picture and a 1 to the second picture, but we wouldn’t be able to say that there are twice as many cookies in the first picture. Just that there are more. Here are some examples of ordinal data.
- A big handful of rice vs a small handful of rice. Why: We don’t know how much rice is in each hand but we can see there is more in one than the other.
- Someone who is a bit shy vs someone who is really shy. Why: We don’t how much more shy the really shy person is, but we know they are more shy.
- Questions on surveys where the answers look like: Strongly agree, somewhat agree, somewhat disagree, strongly disagree. Why: We don’t know how much more “strongly” is compared to “somewhat” but we do know it’s more.
- This is more than that. This is lighter than that. This is heavier than that. This is taller than that. This is bluer than that. This is tastier than that. This feels more rough than that. This smells worse than that. This is longer than that. This is earlier than that. This is faster than that.
- Something is more or less than the other thing
- We don’t know how much more or less it is
- Social Media Data is like a Box of Timbits
- Really Simple Statistics: T-Tests
- Really Simple Statistics: p values
- Really Simple Statistics: Nominal Ordinal Interval and Ratio Numbers