The most commonly used terms to describe data are Nominal, Ordinal, Interval and Ratio. They have been used very extensively and not only have they been used to describe the data but also to decide the most appropriate statistical test to use. They can be explained as here:

**Nominal: **when we talk of discrete data we talk of nominal scale. For example, name of school, car and book. If one has to remember what nominal data is, it is easy to remember as it has the same Latin root of name and that is what it derives from the respondents.

**Ordinal: **This scale talks about those quantitates that have natural ordering. However, in ordinal data it is difficult to state with complete certainty if the intervals between the values are equal. Often in this case, Likert type questions are used as rating scale and 9 and 10 on a 10 point rating scale may not be same as the difference between 6 and 7. When it comes to remember this one, ordinal sounds like order so the retention is easier.

**Interval: **This kind of data is similar to ordinal data, the only difference being that the intervals between the values are split equally. One of the most common examples of this would be temperatures in degrees Fahrenheit. The difference between 29 and 30 degrees has the same magnitude as 78 and 79. Many times scales are of equal intervals.

**Ratio:** It is an extension of the interval data but has a natural zero point. The zero point should also haves some meaning to it. Time is considered to be a ratio because 0 time has some meaning to it. The degree of magnitude remains the same for both these steps