We are aware that the data can be divided into primary and secondary data. Further data can be classified according to their properties. What is classification? Classification is the process of arranging data into sequences and groups according to their common characteristics or separating them into different related parts.
The functions of classification are condensation of data, comparison of data, relationship study and statistical treatment. If we consider the rules of classification, it should be unambiguous, it should be exhaustive and mutually exclusive, stability, suitability and flexibility. The criteria in which the data can be classified are, Geographical, Chronological, Qualitative and Quantitative. In this section let us study about quantitative study which is with respect to numerical values and magnitudes.

## Types of Quantitative Data

If the data are classified on the basis of phenomenon which is capable of quantitative measurement like age, height, weight, prices, production, income, expenditure, sales, profits, etc, it is termed as quantitative classification. The quantitative phenomenon under study is known as variable and hence this classification is also some times called classification by variables.

Let us consider the following table:

 Marks No. of students 0 - 20 10 20 - 40 12 40 - 60 18 60 - 80 15 80 - 100 5

The above table shows the marks scored by 60 students in a class.
The above frequency distribution has 2 elements
1. Variable (Marks)
2. Frequency (No. of students)
Variables are of two kinds
They are,
1. Discrete Variable (Discrete Data)
2. Continuous Variable (Continuous Data)

## Discrete Data

The variables which cannot take all the possible values within a given specified range are termed as discrete (discontinuous) variables. For example, the marks in a test (out of 100) of a group of students is a discrete variable since in this case marks can take only integral values from 0 to 100 (usually marks out of 100 are rounded to the nearest integer).

The other examples are population of a town, number of accidents on the road, the number of typing mistakes per page and so on.

Table of data showing Discrete Data:

The following table represent the number of wickets a player scored in different test matches.
 No. of wickets No. of Matches 0 5 1 12 2 13 3 6 4 9

As the number of wickets can not be expressed in fractional form, we can tabulate the data in discrete form.

## Continuous Data

The variables which can take all the possible values (integral as well as fractional) in a given specified range are termed as continuous variables.

For example, the age of students in a school is a continuous variable because age can take all possible values (as it can be measured to the nearest fraction of time : years, months, days, minutes, seconds etc.)

Other examples of continuous variables are height in (feet and inches), weight (in lbs), distance (in kms).

More precisely a variable is said to be continuous if it is capable of passing from any given value to the next value by infinitely small gradations.

Example of Continuous Data:
The following table represent the number of students whose height is expressed as an integral or a fraction.
 Height (in inches) No. of Students 60 - 65 6 65 - 70 15 70 - 75 17 75 - 80 13 80 - 85 5

As the height in inches can be expressed in fraction we can express the data in continuous data form.