Data Collection and data presentation in research methodology

1. Data collection techniques
&
Presentation of data
Anupta Jana
anuptajana@gmail.com
SLIS,GM University
29-06-2021

2. Introduction
In research work it is necessary to measure various
characteristics.

3. What are the Characteristics?
• Age, Height, Income, Education level, etc.
• All are not similar.

4. Variables
Qualitative
Social behaviour
& Personality
Cultural &
Social
environment
Quantitative
Discrete
Continuous

5. How to measure ?

6. Data
Collection
Techniques
Questionnaire
Interview
Observation
Sampling
Delphi

7. Questionnaire
• A set of questions designed to generate the statistical information from the
respondent in a research.
• Types
• Open ended / Unstructured
• Close ended /
• Mixed

8. Open ended questionnaire
• Freedom to express
• Avoid bias
• More information
• Unstructured
• Difficulties in statistical analysis

9. Close ended questionnaire
• Limited freedom to express
• Structured
• Easy to statistical analysis

10. Mixed questionnaire
• Mixture of open ended and close ended questionnaire.

11. Interview
• Verbal conversation between two people with the aim of data
collection in a research.

12. Types of Interview
Personal Interview Telephone Interview Web Interview

13. Observation
• Observing or studying an object or person in a systematic way with the
aim of specific objectives in research
• Effective way of collecting data
• But time consuming

14. Sampling
• Sampling frame
• A list of all units of the population of interest
• Ex. - People, organisations, documents
• Types
• Probability
• Non-probability

15. Probability sampling

16. Non-Probability sampling

17. Delphi method

18. How to present the collected data?

19. Data
Presentation
Tabular
Nominal &
Ordinal
Numerical
Graphical
Line
Histogram
Frequency
polygon
Frequency curve
Bar diagrams
Pie chart

20. Tabular
• Nominal & Ordinal
• Numerical

21. Frequency distribution
• A table or graph that displays the frequency of various outcomes in a
sample.
Class Frequency
Class 10 2
Class 11 3
Class 12 4
Class 10
Class 11 Class 12

22. Types of frequency distribution
• Cumulative frequency
• Cumulative Relative frequency / Relative frequency

23. Line graph
• To show an increase or decrease of a variable over time or throughout
observation
76
85 86
90
82
98
105 108 110
115 118
106
0
20
40
60
80
100
120
140
January
February
March
April
May
June
July
August
September
October
November
December
Number of visitors corresponding to months

24. Histogram
• Histogram is a rectangular diagram.
• The area of each rectangle is proportional to the frequency of the respective class.
• Continuous distribution
21
32
49
33
23
12
5
0
10
20
30
40
50
60
100-200 200-300 300-400 400-500 500-600 600-700 700-800
Frequency
Class interval
Histogram

25. Frequency polygon
• By joining the mid value of the top of the rectangles with the help of
straight lines.

26. Frequency curve
• A smooth curve which corresponds to a histogram computed for a
frequency distribution of a continuous distribution.
21
32
49
33
23
12
5
0
10
20
30
40
50
60
Frequency
Class interval
Frequency Curve

27. Bar diagram
• Categorical data are presented with rectangular bars.
• Hight or length of the bars are proportional to the value of the categories.
• Appropriate for qualitative data
800
460
520
0
100
200
300
400
500
600
700
800
900
arts science commerce
no. of students

28. Pie chart
• To show the share of different components in a variable
• Circle has 360o
Salary, 246, 24%
Books, 325, 32%
Journals, 175,
17%
Furniture, 200,
19%
Maintenance, 50,
5%
Contingency, 30,
3%
100
Budget
Component
TotalBudget
 
360
Budget
Degree
TotalBudget
 

29. Summary
• Variable
• Types of variable
• Data collection techniques
• Data presentation

30. Reference
• Unit-6 Measurement of Variables. (2017). IGNOU.
http://egyankosh.ac.in//handle/123456789/11217
• Unit-7 Data Presentation. (2017). IGNOU.
http://egyankosh.ac.in//handle/123456789/11213

31. Thank you