Chronological Classification of Data refers to the classification of data with reference to time intervals which may be measured in years, months, etc. Most business and economic data are usually classified chronologically in the form of a time series. Arranging data in the form of a time series allows us to analyze past data values in order to make future predictions.
We now give some examples of raw data organized chronologically in the form of a time series. The data values are usually presented in ascending order from the first year to the last.
Example 1:
The annual sales of a company for a certain number of years is an example of the chronological classification of data. Suppose that we are given the annual sales made by a company from year to year as follows:
| Year | Sales (in thousands) |
| 1993 | 20 |
| 1994 | 24 |
| 1995 | 22 |
| 1996 | 30 |
| 1997 | 28 |
| 1998 | 32 |
In the above example, we have divided the total sales of the company by the sales made in each unit interval of time (one year). The above data can also be plotted graphically as follows,
Notice that if we plot a trend line as shown in the above diagram, it can be used in order to make predictions about future values. If the trend line is extended a bit further it allows us to make a rough prediction for the expected future sales of the company in 1999.
Example 2:
Suppose that a school publishes annual data about the percentage of ninth-grade students who receive a failing grade on the final exam. Here since the data is classified on the basis of the academic year. Consider the data as shown below,
| Academic Year | Percentage of Failing Students |
| 2015 | 12% |
| 2016 | 10% |
| 2017 | 7% |
| 2018 | 7% |
| 2019 | 6% |
Looking at the above time series data we can conclude that the performance of the students is getting better year after year. Thus we see that it is a very useful practice to classify data in units of time since it allows us to make comparisons between past and future data values.
