Ordinal is used to denote the order of things or the ranking of items. For example, if we were to analyze a set of reviews and rank them from most positive to most negative, we would be using ordinal data.
Advantages of using Ordinal Data
The advantage of ordinal data is its ability to show relationships between items. When comparing two things, we can see which one is better or worse than the other. For example, if we were looking at a set of reviews for two different products, we could use ordinal data to compare the overall sentiment of the reviews. If the sentiment of the reviews for one product was consistently ranked higher than the other, we could conclude that the first product is generally seen as being better than the second product.
Limitations Using Ordinal Data
ordinal data may have an advantage in comparing relationships of a data, but it has also a few limitations. First, it is difficult to quantify relationships between items. For example, if we were looking at a set of reviews and one had a sentiment score of 3 and the other had a sentiment score of 5, we could say that the first review is more positive than the second, but we couldn’t say by how much. Second, ordinal data is often subjective. What one person sees as being positive may be seen as being negative by someone else. This can make it difficult to draw objective conclusions from ordinal data.
Ordinal Data vs. Cardinal Data
Ordinal data is sometimes confused with cardinal data, which is a measure of quantity. However, cardinal data does not involve ranking or ordering items.
Ordinal Data vs. Relative Data
Another term that is sometimes used in place of ordinal data is relative data. Relative data is similar to ordinal data in the context that it involves ranking or ordering items. However, relative data does not have a fixed scale and can therefore be more subjective.