Collection and Classification of Data

Suresh Babu G
Assistant Professor
CTE CPAS Paippad, Kottayam
Collection and
Classification of Data

Collection of Data
Primary
Data
Secondary
Data
Data are collected from two sources
Sources of Data
Date is the collection of facts or information from which conclusion may be drawn

Primary Data
• The enumerator (person who collects the data)
may collect the data by conducting an enquiry or
an investigation. Such data are called primary
data.
• It is also known as first hand data.
• Example : A teacher conduct a test and collect
data as mark.

Secondary Data
• The data have been collected and processed
(scrutinized and tabulated) by some other
agency are called secondary data.
• Sources of secondary data are government
reports, documents, newspapers, magazine etc..
• Example – teacher collect data from anecdotal
records.

Mode of Data Collection
• Personal interviews – Investigator conducts
face to face interviews with the respondents.
• Mailing Questionnaire – sending questionnaire
through mail with a request to complete and
return it in the given date.
• Telephone Interviews – investigator asks
questions over the telephone.
Personal interviews
Mailing
Questionnaire
Telephone
Interviews

Collection of Primary Data
• Census or Complete Enumeration Method –
A survey which includes every element of the
population.
• Sampling Method – Here a section or group of
the population is taken for study.

Types of Sampling
• Random Sampling – individual units from the
population are selected at random. In random
sampling every individual has an equal chance
of being selected.
• Non-Random Sampling – All the units of the
population do not have an equal chance of being
selected.
Types of Sampling

• Chronological Classification – classification
based on time such as years, months etc.
• Spatial Classification – classification based on
geographical locations such as countries, states,
districts etc.
• Quantitative Classification – classification of
data based on quantity like height, weight, age etc.
• Qualitative Classification – classification of data
based on attributes or qualities such as religion,
gender, literacy etc.

Grouped and Ungrouped Data
 Ungrouped Data : The data obtained in original
form are called raw data or ungrouped data.
Example : Marks obtained by 10 students in a
class in an examination is; 25, 8, 37, 16, 45, 40,
29, 12, 42, 14.
 Any arrangement of ungrouped data in
ascending or descending order of magnitude is
called an array or called discrete series.

Marks obtained a test of maximum score of 5 by
20 students are given make a frequency array.
1, 2, 2, 1, 3, 4, 5, 5, 3, 2, 2, 3, 4, 3, 4, 1, 3, 3, 4, 4
Marks Tally No of
students
1 lll 3
2 llll 4
3 llll l 6
4 llll 5
5 ll 2
Total 20
Frequency Array

• Grouped Data (Continuous series) – To put the
data in a more condensed form, we make
groups of suitable size, and mention the
frequency of each group. Such table is called
grouped frequency distribution table.
Frequency Distribution Table
Marks obtained a test of maximum score of 25
by 20 students are given make a frequency
distribution table.
24, 1, 10, 21, 20, 4, 16, 5, 14, 2, 13, 20, 11,
8, 15, 9, 10, 17, 19, 22

Steps
1. Find the range (R)
R = Highest value - Lowest value
Here R = 24 – 1 = 23
2. Estimate number of class or
intervals k
K = n where n number of observations
Note : If the resulting value is fractional,
then we take the next higher integer.
K = 20 = 5

3. Estimate the class width c of each interval
C = R/k
Note : Round off the answer to the same number
of decimal places that the observations have.
C = 23/5 = 4.6 = 5

4. List the lower and upper class limits of the fist
interval.
5. List all succeeding lower and upper class limits
by adding the class with c to the lower limit of
the first class interval. The upper class limit of
the first interval should be the number before
the lower class interval of the second interval.
Class interval (Class Mark)
0 – 5
5 – 10
10 – 15
15 – 20
20 - 25

6. From the data, tally the observations according
to the interval which it belongs to. Summarize
the tallies in a column for the frequencies.
Class Mark Tally Frequency
0 – 5 lll 3
5 – 10 lll 3
10 – 15 llll 5
15 – 20 llll 4
20 - 25 llll 5
Total 20

7. Compute the class marks and class boundaries
Class Mark = (lower class limit + Upper class limit)
÷ 2
Class
Mark
Tally Frequency Class mark
0 – 5 lll 3 2.5
5 – 10 lll 3 7.5
10 – 15 llll 5 12.5
15 – 20 llll 4 17.5
20 - 25 llll 5 22.5
Total 20

Conversion of Inclusive into
Exclusive
Lower limit – 0.5 and Upper limit + 0.5
Marks Frequency
0 - 9 2
10 - 19 5
20 - 29 2
30 - 39 1
Marks Frequency
0.5 – 9.5 2
9.5 – 19.5 5
19.5 – 29.5 2
29.5 – 39.5 1
Inclusive Data Exclusive Data

Need and purpose of
• In the construction and standardization of various tests
and measures.
• In making proper use of the results of various tests
and measures.
(i) To know individual difference of our students.
(ii) To compare the stability of our method and
techniques
(iii) To make comparison of system of evaluation
(iv) To compare the function and work.
(v) To make perdition regarding the future of students.
(vi) To make selection
(vii) For easy identification

Collection and Classification of Data

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