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Presentation of Data
Page 2


Presentation of Data
1) Presentation of Data
1.1) Tabular presentation
1.1.a) Components of table
1.1.b) Features of a good table
1.1.c) Kind of tables
1.1.d) Classification of data and  
Tabular Presentation 
Page 3


Presentation of Data
1) Presentation of Data
1.1) Tabular presentation
1.1.a) Components of table
1.1.b) Features of a good table
1.1.c) Kind of tables
1.1.d) Classification of data and  
Tabular Presentation 
1.2) Textual presentation
1.3) Diagrammatic presentation
1.3.a) Bar diagrams
1.3.a.i) Types of Bar diagrams
1.3.a.i.A) Simple Bar diagrams
1.3.a.i.B) Multiple Bar diagrams
1.3.a.i.C) Sub-divided Bar diagrams
1.3.a.i.D) Percentage Bar diagram
Page 4


Presentation of Data
1) Presentation of Data
1.1) Tabular presentation
1.1.a) Components of table
1.1.b) Features of a good table
1.1.c) Kind of tables
1.1.d) Classification of data and  
Tabular Presentation 
1.2) Textual presentation
1.3) Diagrammatic presentation
1.3.a) Bar diagrams
1.3.a.i) Types of Bar diagrams
1.3.a.i.A) Simple Bar diagrams
1.3.a.i.B) Multiple Bar diagrams
1.3.a.i.C) Sub-divided Bar diagrams
1.3.a.i.D) Percentage Bar diagram
1.3.b) Pie diagram
1.3.c) Frequency Diagrams
1.3.c.i) Histogram
1.3.c.i.A) Unequal
1.3.c.i.B) Equal
1.3.c.ii) Polygon
1.3.c.iii) Frequency curve polygon
1.3.c.iv) Ogive or Cumulative    
Frequency Curve
Page 5


Presentation of Data
1) Presentation of Data
1.1) Tabular presentation
1.1.a) Components of table
1.1.b) Features of a good table
1.1.c) Kind of tables
1.1.d) Classification of data and  
Tabular Presentation 
1.2) Textual presentation
1.3) Diagrammatic presentation
1.3.a) Bar diagrams
1.3.a.i) Types of Bar diagrams
1.3.a.i.A) Simple Bar diagrams
1.3.a.i.B) Multiple Bar diagrams
1.3.a.i.C) Sub-divided Bar diagrams
1.3.a.i.D) Percentage Bar diagram
1.3.b) Pie diagram
1.3.c) Frequency Diagrams
1.3.c.i) Histogram
1.3.c.i.A) Unequal
1.3.c.i.B) Equal
1.3.c.ii) Polygon
1.3.c.iii) Frequency curve polygon
1.3.c.iv) Ogive or Cumulative    
Frequency Curve
1.3.c.iv.A) Less than Ogive
1.3.c.iv.B) More than Ogive
2.) Some Questions
2.1) Very Short Answer Type 
Questions
2.2) Short Answer Type Questions
2.3) Long Answer Type Questions
2.4) Numerical Questions
Read More
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FAQs on PPT - Presentation of Data - General Aptitude for GATE - Mechanical Engineering

1. What is data commerce?
Ans. Data commerce refers to the buying and selling of data as a commodity. It involves collecting, analyzing, and monetizing data to generate insights and make informed business decisions.
2. How can data commerce benefit businesses?
Ans. Data commerce can benefit businesses in several ways. It provides valuable insights into customer behavior, market trends, and competitive intelligence, enabling businesses to optimize their strategies, improve decision-making, and drive growth. It can also create new revenue streams through the sale of data to other organizations.
3. What are the ethical considerations in data commerce?
Ans. Ethical considerations in data commerce include ensuring data privacy and security, obtaining proper consent from individuals whose data is being collected, and using data in a responsible and transparent manner. Businesses should comply with relevant data protection laws and regulations and prioritize the protection of personal information.
4. How can businesses ensure the quality of data in data commerce?
Ans. To ensure the quality of data in data commerce, businesses should implement robust data collection and verification processes. This may involve using reliable data sources, employing data cleaning and validation techniques, and regularly updating and maintaining data accuracy. Quality control measures should be in place to minimize errors and inconsistencies.
5. What are some challenges in data commerce?
Ans. Some challenges in data commerce include data privacy concerns, data security risks, data integration difficulties, and data quality issues. Additionally, the increasing volume and complexity of data pose challenges in terms of data storage, processing, and analysis. Businesses also need to navigate legal and regulatory frameworks governing data commerce.
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