Meaning and Objectives of Classification of Data

●     A variable refers to a quantity or attribute whose value varies from one investigation to another.

●     Example:

1. “Price” is a variable as prices of different commodities are different.
2. “Age” is a variable as the ages vary
3. Some more examples are: height, weight, wages, expenditure, import, production, etc.

●     For example, the number of workers or the number of students in a class is a discrete variable as they cannot be in fraction. Similarly, the number of children in a family can be 1, 2, and so on, but cannot be 1.5, 2.75.

●     For example, temperature, height, weight, marks, etc.

Following are the basis of classification:

●     It is also known as ‘spatial classification’.

●     In such a classification, data are classified either in ascending or in descending order with reference to time such as years, quarters, months, weeks, etc.

●     It is also known as temporal classification’.

●     For example, the population can be divided on the basis of marital status (as married or unmarried)

(i) Time series (Chronological series)

If the different values that a variable has taken in a period of time are arranged in a chronological order, the series so obtained is known as a time series.

(ii) Spatial series (Geographical series)

The data arranged according to location or geographical considerations form a spatial series.

(iii) Condition series

In this series, data are classified according to the changes occurring in variables according to a condition, such as height, weight, age, marks, income, etc.

(i) Individual series

Individual series refers to a series in which items are listed singly, i.e., each item is given a separate value of the measurement. Example:

A discrete series is a series where individual values differ from each other by a definite amount.

Example:

A continuous series is a series that represents continuous variables, showing a range of values of different items of the series. Example:

●     The upper limit of one class becomes the lower limit of the next class.

●     For grouping or counting the number of observations, lower limit (l1) is considered but upper limit (l2) is not considered/included.

– There are five classes..

– Class size = l2– l1 = 10 (for all)

– Mid-value = (l2  + l1) ÷ 2

●     The upper limit of one class is not equal to the lower limit of the next class.

●     For grouping or counting the number of observations, lower limit (l1) and upper limit (l2) are not considered/included.

●     Mid-value or mid-point is the central value of a class -interval.

●     When such mid-values are given, it is known as the mid-value series.

●     It can be converted into equal interval distribution by:

●     Merging the classes;

●     Splitting the classes.

“Less than Cf distribution”

●     It is obtained by successively adding the frequencies of the values of the classes.

Classification of data is the process of arranging data in groups or classes on the basis of certain properties.

When data are classified according to a geographical location or region, it is known as geographical classification.

When data is classified on the basis of characteristics that can be measured, it is known as quantitative classification.

When data is classified on the basis of attributes, it is known as qualitative classification.

(i) Time series;

(ii) Spatial series;

(iii) Condition series.

‘Class’ means a group of numbers, in which items are placed, such as 0–-10, 10–-20, 20–-30, etc.

●     The two extreme values of each class are known as the class limits.

●     The lowest value is termed as the ‘lower limit’ (l2), and the highest value is known as the upper limit’ (l2) of the class.

●     For example, in the class “5–-10”, 5 is the lower limit (l1) and 10 is the upper limit (l2).

●     The difference between the upper limit (l2) and the lower limit (l1) of a class is known as the magnitude of the class or class size.

●     For example, in the class -interval 20–-50, the magnitude of class -interval is (l2– l1), i.e., 50 – 20 = 30.

Exclusive series.

●     Mid-point is the central point of a class -interval, which lies halfway between the lower and upper-class limits. It is (l1 + l2) ÷ 2.

●     For example, the mid-point of class 10–-20 will be: Mid-point = (10 + 20) / 2 = 15.

Inclusive method.

Frequency refers to a number of times a given value appears in a distribution.

A table, in which the frequencies and the associated values of a variable are written side by side, is known as a frequency distribution.

A mass of data in its original form is known as raw data.

Continuous series.

b. To present data in a simple, logical, and understandable form.

c. To bring out points of similarity and dissimilarity among various groups.

d. All of the above

b. Continuous variables

c. Both a. and b.

d. None of the above