Ordinal Data vs. Interval Data

Difference Between Ordinal Data and Interval Data

Ordinal and Intervals are data types and are ways to represent and classify information. These data types are used for measuring different aspects of the information by using statistics. It is important for you to understand these two types of data representation if you are into research.

Ordinal Data is arrangement of data in terms of X and Y axis on a scale. The data on both these axis is then correlated and studied.  For example if you have to correlate the passing percentage of a college in different years then you can put number of years on  x axis and number of students who passed, on Y axis. This way you can easily compare the passing percentage in different years.

Interval data is arrangement of data on a continuous scale and the value of data will differ from each other equally. For example in the first value is 10 and the next value is 20 then the next values will be 30, 40, 50 etc so that the interval between these values remains same.  This helps in projecting the information very easily in terms of comparative scale.

We can convert the interval data into ordinal data by arranging the intervals on the basis of ranks. Interval data is more informative than ordinal data. Ordinal data is always arranged on the basis of ranks. Here the gap between the values may not be same while this gap is same in case of interval data. This uniformity of data in interval data makes it different from ordinal data.

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