Meaning and Objectives of Classification of Data

Meaning of Classification of Data

  • It is the process of arranging data into homogeneous (similar) groups according to their common characteristics.
  • Raw data cannot be easily understood, and it is not fit for further analysis and interpretation. This arrangement of data helps users in comparison and analysis.
  • For example, the Population of town can be grouped according to sex, age, marital status etc.

Classification of data

The method of arranging data into homogeneous classes according to some common features present in the data is called classification.

A planned data analysis system makes fundamental data easy to find and recover. This can be of particular interest for legal discovery, risk management and compliance. Written methods and set of guidelines for data classification should determine what levels and measures the company will use to organise data and define the roles of employees within the business regarding input stewardship. Once a data-classification scheme has been designed, security standards that stipulate proper approaching practices for each division and storage criteria that determine the data’s lifecycle demands should be discussed.

Objectives of Data Classification

The primary objectives of data classification are:

  • To consolidate the volume of data in such a way that similarities and differences can be quickly understood. Figures can consequently be ordered in a few sections holding common traits.
  • To aid comparison.
  • To point out the important characteristics of the data at a flash.
  • To give importance to the prominent data collected while separating the optional elements.
  • To allow a statistical method of the material gathered.
Definition of Classification Given by Prof. Secrist “Classification is the process of arranging data into sequences according to their common characteristics or Separating them into different related parts.”


Q.- What is Meant by Variable? Briefly Explain Its Two Kinds.
(a) Meaning of Variable
  • The term variable is derived from the word ‘vary’ which means to differ or change. Hence, variable means the characteristic which varies or differs or changes from person to person, time to time, place to place etc. Or
  • A variable refers to quantity or attribute whose value varies from one investigation to another.
  • For example:
  1. “Price” is a variable as prices of different commodities are different.
  2. “Age” is a variable as the age of different students varies.
  3. Some more examples are Height, Weight, Wages, Expenditure, Imports, Production, etc.
(B) Kinds of Variable:
(I) Discrete Variable
  • Variables which are capable of taking an only exact value and not any fractional value are termed as discrete variables.
  • For example, a number of workers or number of students in a class is a discrete variable as they cannot be in fraction. Similarly, a number of children in a family can be 1, 2 or so on, but cannot be 1.5, 2.75.
(II) Continuous Variable
  • Those 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, Temperature, Height, Weight, Marks etc.

Methods of Classification

Q.- Briefly Explain the Basis or Methods of Classification.

Following Are the Basis of Classification:

(1) Geographical Classification
  • When data are classified with reference to geographical locations such as countries, states, cities, districts, etc. it is known as Geographical Classification.
  • It is also known as ‘Spatial Classification’.
(2) Chronological Classification
  • When data are grouped according to time, such a classification is known as a Chronological 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 called ‘Temporal Classification’.
(3) Qualitative Classification
  • Under this classification, data are classified on the basis of some attributes or qualities like honesty, beauty, intelligence, literacy, marital status etc.
  • For example, Population can be divided on the basis of marital status as married or unmarried etc.
(4) Quantitative Classification
  • This type of classification is made on the basis some measurable characteristics like height, weight, age, income, marks of students, etc.

Statistical Series

Q.- What is a Statistical Series? Briefly Discuss the Various Kinds of Statistical Series.
(a) Statistical Series
  • Statistical series is a systematic arrangement of statistical data in some logical order.
(B) Statistical Series Can Be Divided as:
(a) On the Basis of General Characteristics On the basis of general characteristics, statistical series are of three kinds:

(i) Time Series (Chronological Series)

If the different values that a variable has taken in a period of time are arranged in chronological order, the series so obtained is called 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 variable according to a condition, such as Height, Weight, Age, Marks, Income etc.

(B) On the Basis of Construction According to construction, statistical series can be categorized as :


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

MARKS (Out of 50) 20 30 10 30 40 50 45 40 42 40

A discrete series is that series where individual values differ from each other by definite amount. Example:

MARKS 12 25 35 45 49
NO. OF STUDENTS 3 5 2 2 1

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

MARKS 0 – 10 10 – 20 20 – 30 30 – 40 40 – 50
NO. OF STUDENTS 1 4 5 6 4

Types of Continuous Series & Their Conversion

Q.- Briefly Discuss the Various Types of Continuous Series.
(a) Exclusive Series Age (in Years) No. of Students
  • Frequency distribution having classes wherein
  • 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.
0 – 10 3
10 – 20 5
20 – 30 12
30 – 40 6
40 – 50 4
In the above example,

– There are 5 Class.

– Class Size = l2– l1=10 (for all)
– Mid Value = (l2 +l1) ÷2

(B) Inclusive Series Age (in Years) No. of Students
  • Frequency distribution having classes wherein
  • 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) & Upper limit (l2), both are not considered/included.
0 – 9 3
10 – 19 5
20 – 29 12
30 – 39 6
40 – 49 4
(C) Mid Value Series Mid Values (f)
  • Mid Value = (l1 + l2) ÷2
  • Mid-value or Mid-point is the central value of a class-interval.
  • When such mid-values are given, it is called mid-value series
5 3
15 5
25 12
35 6
45 4
(D) Open Ended Series (Distribution) Age (in Years) No. of Students
  • In a frequency distribution, if the lower limit (l1) of the first class and the upper limit (l2) of last class is not given, it is called “Open-End Distribution”.
BELOW 10 3
10 – 20 5
20 – 30 12
30 – 40 6
40 & ABOVE 4
(E) Continuous Series With Unequal Interval (X) (f)
  • When the class size i.e. the gap between (l2) & (l1) is not equal is all the classes, it is called Unequal Class Interval Series.
  • It can be converted into Equal Interval Distribution by either
  • Merging the classes; or
  • Splitting the classes.
0 – 10 3
10 – 15 5
15 – 30 12
30 – 40 6
40 – 45 4
(F) Cumulative Frequency Distribution-

“Less Than Cf Distribution”

Age (in Years) No. of Students
  • Cumulative frequency series is a modification of the simple frequency distribution.
  • It is obtained by successively adding the frequencies of the values of the classes.
Less Than 10 3
Less Than 20 8
Less Than 30 20
Less Than 40 26
Less Than 50 30
“More Than Cf Distribution” Age (in Years) No. of Students
More Than 10 30
More Than 20 27
More Than 30 22
More Than 40 10
More Than 50 4
Short Questions:
Q.1- What is Meant by Classification of Data?

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

Q.2- What is Meant by Geographical Classification?

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

Q.3- What is Quantitative Classification?

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

Q.4- Define Qualitative Classification.

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

Q.5- Give the Names of Statistical Series on the Basis of Construction.

(i) Time Series;
(ii) Spatial Series; and
(iii) Condition Series.

Q.6- What is a Class?

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

Q.7- What Do You Understand by the Class Limits?

  • The two extreme values of each class are called class limits.
  • The lowest value is termed as ‘Lower limit’ (l2), and the biggest value is called as ‘Upper limit’ (l2) of a class.
  • For example, in the class “5-10”, 5 is the lower limit (l1) and 10 is the upper limit (l2).
Q.8- What is Meant by Magnitude of a Class?

  • The difference between the upper limit (l2) and lower limit (l1) of a class is called magnitude of the class or Class Size.
  • For example, in the class-interval 20-50, magnitude of class-interval is (l2l1) i.e. 50 – 20 = 30.
Q.9- Which Series Exclude the Upper Limit of the Class-interval?
Answer: Exclusive Series.
Q.10- What is Meant by Mid-point?

  • Mid-point is the central point of a class-interval, which lies halfway between lower and upper-class limits. It is (l1 + l2) ÷2.
  • For example, mid-point of class 10-20 will be: Mid-point = (10+20) / 2 = 15.
Q.11- Which Method Includes Both the Class Limits in the Class of a Continuous Series?
Answer: Inclusive Method.
Q.12- What is Meant by the Term ‘frequency’?

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

Q.13- What is a Frequency 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.

Q.14- What Do You Understand by Raw Data?
Answer: A mass of data in its original form is known as raw data.
Q.15- Name the Series, Which Have Class-interval.
Answer: Continuous Series.

Multiple Choice Questions:

Q.1- Which of the following is the objective of classification
a. To condense the mass of data.

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

Q.2- Temperature, Height, Weight, Marks are an example of
a. Discrete Variable

b. Continuous Variable

c. Both a and b

d. None of the above

Answer Key
1-d, 2- b Fill in the Blanks
1 _________ of data is the process of arranging data into homogeneous groups according to their common characteristics. Answer Key
1 Classification

The above-mentioned concept is for CBSE Class 11 Statistics for Economics – Meaning and Objectives of Classification of Data. For solutions and study materials for Class 11 Statistics for Economics, visit BYJU’S or download the app for more information and the best learning experience.


  1. This is a Very nice app to learn and make notes of any chapter

  2. Ashwathi devi sunil

    So nice

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