PPT - Presentation of Data | General Aptitude for GATE - Mechanical Engineering PDF Download

 Page 1


Presentation of 
Data
Page 2


Presentation of 
Data
Introduction
1
Textual or 
Descriptive 
presentation
Data described within 
text. Best for small 
data quantities.
2
Tabular 
presentation
Data organized in 
rows and columns for 
easier comparison 
and analysis.
3
Diagrammatic 
presentation
Visual elements like 
charts and graphs 
that enable quick 
understanding.
Page 3


Presentation of 
Data
Introduction
1
Textual or 
Descriptive 
presentation
Data described within 
text. Best for small 
data quantities.
2
Tabular 
presentation
Data organized in 
rows and columns for 
easier comparison 
and analysis.
3
Diagrammatic 
presentation
Visual elements like 
charts and graphs 
that enable quick 
understanding.
Textual Presentation 
of Data
Textual presentation describes data within 
written content. This method is most effective 
when working with smaller data quantities.
Advantages
Emphasizes key points and provides 
essential context for the presented data.
Limitations
Requires reading the entire text to fully 
comprehend the information presented.
Page 4


Presentation of 
Data
Introduction
1
Textual or 
Descriptive 
presentation
Data described within 
text. Best for small 
data quantities.
2
Tabular 
presentation
Data organized in 
rows and columns for 
easier comparison 
and analysis.
3
Diagrammatic 
presentation
Visual elements like 
charts and graphs 
that enable quick 
understanding.
Textual Presentation 
of Data
Textual presentation describes data within 
written content. This method is most effective 
when working with smaller data quantities.
Advantages
Emphasizes key points and provides 
essential context for the presented data.
Limitations
Requires reading the entire text to fully 
comprehend the information presented.
Examples of Textual Presentation
Case 1
In a bandh call given on 08 September 
2005 protesting the hike in prices of petrol 
and diesel, 5 petrol pumps were found 
open and 17 were closed whereas 2 
schools were closed and remaining 9 
schools were found open in a town of 
Bihar.
Case 2
In 2001, India's population was 102 crore - 
49 crore women, 53 crore men. 74 crore 
lived rurally, 28 crore in towns/cities. 62 
crore were non-workers, 40 crore were 
workers. Urban areas had 19 crore non-
workers, 9 crore workers. Rural areas had 
31 crore workers out of 74 crore.
Page 5


Presentation of 
Data
Introduction
1
Textual or 
Descriptive 
presentation
Data described within 
text. Best for small 
data quantities.
2
Tabular 
presentation
Data organized in 
rows and columns for 
easier comparison 
and analysis.
3
Diagrammatic 
presentation
Visual elements like 
charts and graphs 
that enable quick 
understanding.
Textual Presentation 
of Data
Textual presentation describes data within 
written content. This method is most effective 
when working with smaller data quantities.
Advantages
Emphasizes key points and provides 
essential context for the presented data.
Limitations
Requires reading the entire text to fully 
comprehend the information presented.
Examples of Textual Presentation
Case 1
In a bandh call given on 08 September 
2005 protesting the hike in prices of petrol 
and diesel, 5 petrol pumps were found 
open and 17 were closed whereas 2 
schools were closed and remaining 9 
schools were found open in a town of 
Bihar.
Case 2
In 2001, India's population was 102 crore - 
49 crore women, 53 crore men. 74 crore 
lived rurally, 28 crore in towns/cities. 62 
crore were non-workers, 40 crore were 
workers. Urban areas had 19 crore non-
workers, 9 crore workers. Rural areas had 
31 crore workers out of 74 crore.
Tabular Presentation of Data
Tabular presentation organizes data into rows and columns, structuring information for 
effective analysis and decision-making. Four main classifications are used in tabulation:
Qualitative
Based on attributes 
like social status, 
nationality, and 
physical 
characteristics.
Quantitative
Based on 
measurable 
characteristics such 
as age, height, 
income, and 
production.
Temporal
Uses time as the 
primary classifying 
variable.
Spatial
Classifies data by 
location: 
village/town, 
district, state, 
country, etc.