Statistical Classifications
Chronological Classification
When data are observed over a time-period the type of classification is termed as chronological classification. For e.g., we may present the figures of population (or sales, production etc.) as follows:
|
year
|
Population (in crores)
|
year
|
Population (in crores)
|
|
1951
|
36.11
|
1981
|
68.33
|
|
1961
|
43.92
|
1991
|
84.64
|
|
1971
|
54.82
|
2001
|
102.87
|
The Time series are usually listed in chronological order, generally starting with the earliest period. When the major emphasis falls on many recent events, a reverse time order may be used.
Quantitative classification
The Quantitative classification refers to the classification of data according to some characteristics that can be measured, such as profits, production, weight, height, income, sales, etc. For e.g., the students of a college may be classified into weight as follows:
|
Weight (in lb.)
|
No. of students
|
|
90-100
|
50
|
|
100-110
|
200
|
|
110-120
|
260
|
|
120-130
|
360
|
|
130-140
|
90
|
|
140-150
|
40
|
|
Total
|
1000
|
Such a distribution is termed as empirical frequency distribution or simple frequency distribution.
In this type of classification, there are 2 elements, namely (i) the variable, i.e. the weight in the example above, and (ii) the frequency, i.e. the no. of students in each class. There are 50 students having the weight ranging from 90 to 100 lb, 200 students having weight ranging from 100 to 110 lb, and so on. Thus we can determine the ways in which the frequencies are distributed.
The following are the two examples of continuous and discrete frequency distributions:
|
No. of children
|
No. of families
|
weight (lb.)
|
no. of persons
|
|
0
|
10
|
100-110
|
10
|
|
1
|
40
|
110-120
|
15
|
|
2
|
80
|
120-130
|
40
|
|
3
|
100
|
130-140
|
45
|
|
4
|
250
|
140-150
|
20
|
|
5
|
150
|
150-160
|
4
|
|
6
|
50
|
|
|
|
Total
|
680
|
Total
|
134
|
|
(a) Discrete frequency distribution
|
(b) Continuous frequency distribution
|