This document discusses the organization and classification of data. It defines classification of data as the process of grouping data according to their characteristics. The objectives of classification are to simplify complex data, facilitate understanding and comparison, and make analysis and interpretation easier. A good classification is comprehensive, clear, homogeneous, suitable, stable and elastic. Qualitative classification divides data based on the existence or absence of qualities, while manifold qualitative classification further divides the data into subgroups. Variables can be discrete, taking whole number values, or continuous, taking values along a range. Statistical series involve arranging raw data into individual series listed numerically or in order, or frequency series which indicate how many observations fall into each class or value.

22. ORGANISATION OF DATA
Organization of data refers to the arrangement of
figures in such a form that comparison of the mass of
similar data may be facilitated and further analysis may
be possible.
This process is called classification of data.
Classification of Data
The process of grouping data according to their
characteristics is known as classification of data.

23. Objectives of Classification:
a] To simplify complex data
b] To facilitate understanding
c] To facilitate comparison
d] To make analysis and interpretation easy.
e] To arrange and put the data according to
their common characteristics.

24. Characteristics of a Good Classification
1.Comprehensiveness
2.Clarity
3.Homogeneity
4.Suitability
5.Stability
6.Elastic

29. Qualitative classification
This classification is according to qualities or
attribute of the data. It can be divided in to two
types.
Simple qualitative classification
The data is divided on the basis of existence or
absence of a quality. For Eg.
Population
Male Female

30. Manifold qualitative classification-
Population
Male Female
literate literateIlliterate Illiterate
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33. Concept of Variable
A characteristic or a phenomenon which is capable of being
measured and changes its value overtime is called variable.
A) Discrete Variable
Discrete variables are those variables that increase in jumps or in
complete numbers. (No fraction is possible)
Eg. Number of students in a class, Number of cars in a show room
etc. (1,2, 10,or 15 etc.)
B) Continuous Variables
Variables that assume a range of values or increase not in jumps but
continuously or in fractions are called continuous variables.
Eg. Height of the boys –5’1’’ , 5’3’’ and so on, Marks in any range 0-
10, 10-15, 15-20

34. Statistical Series: Systematic arrangement of statistical data-
Raw data: Data collected in original or crude form.
Series: Arranging of raw data in different classes according to a given
order or sequence is called series.
Conversion of Raw Data into Series
1. Individual Series without frequency
2. Frequency series or Series with frequencies.

35. 1] Individual Series: The arrangement of raw data individually
Individual Series can be expressed in two ways.
a] According to Serial Numbers-
Roll Number Marks
1 30
2 25
3 15
4 30
5 25
b] Ascending or descending order.
In ascending order, smallest number is placed first. For Eg. Marks- 30,25,15
In descending order, the highest number is placed first. For Eg. Marks- 15,20,30

36. 2) Frequency Series
Two types-
1. Discrete Series or Frequency Array (tally bars). No class interval-
A series is called discrete if the variable can take only some particular values.
2. Frequency Distribution (tally bars) with class interval-
A series is called continuous if it can take any value in a given range.
Marks 11 12 13 14
No. of
Students
5 7 9 3
Marks 0-10 10-20 20-30 30-40
No. of
Students
5 7 9 3

37. In constructing continuous series we come across terms like:
a] Class : Each given internal is called a class e.g., 0-5, 5-10.
b] Class limit: There are two limits upper limit and lower
limit.
c] Class interval: Difference between upper limit and lower
limit.
d] Range: Difference between upper limit and lower limit.
e] Mid-point or Mid Value: Upper limit -Lower limit
2
f] Frequency: Number of items [observations] falling within a
particular class.

40. Cumulative Frequency Series:
It is obtained by successively adding the frequencies of the values of the classes
according to a certain law.
a] ‘Less than’ Cumulative Frequency Distribution :
The frequencies of each class-internal are added successively starting from the
lowest value of the variable.
b] ‘More than’ Cumulative Frequency Distribution:
The frequencies of each class interval are added successively starting from the
highest value of the variable to the lowest value.

41. Mid value series-
In this series we have only mid values of the class
intervals and the corresponding frequencies.
Mid Value 5 15 25 35 45
Frequency 2 5 7 8 2