PPT: Sources-Acquisition & Classification of Data | Data Interpretation for UGC NET PDF Download

 Page 1


Sources, 
Acquisition & 
Classification of 
Data
Page 2


Sources, 
Acquisition & 
Classification of 
Data
Data Interpretation
What is Data 
Interpretation?
The act of organizing and 
interpreting data to extract 
meaningful information. It involves 
drawing conclusions from data 
presented numerically in tabular or 
graphical form.
Required Skills
Good knowledge of percentage, 
ratio, proportion, and average 
concepts. Familiarity with graphical 
representations like Venn 
diagrams, graphs, pie-charts, 
histograms, and polygons.
Data vs Statistics
Data are individual pieces of factual information recorded for analysis - the 
raw information. Statistics are the results of data analysis through 
interpretation and presentation.
Data interpretation tests not only quantitative skills but also relative, comparative, 
and analytical abilities. With practice and familiarity with different data 
representations, questions based on tables and graphs can be answered 
efficiently.
Page 3


Sources, 
Acquisition & 
Classification of 
Data
Data Interpretation
What is Data 
Interpretation?
The act of organizing and 
interpreting data to extract 
meaningful information. It involves 
drawing conclusions from data 
presented numerically in tabular or 
graphical form.
Required Skills
Good knowledge of percentage, 
ratio, proportion, and average 
concepts. Familiarity with graphical 
representations like Venn 
diagrams, graphs, pie-charts, 
histograms, and polygons.
Data vs Statistics
Data are individual pieces of factual information recorded for analysis - the 
raw information. Statistics are the results of data analysis through 
interpretation and presentation.
Data interpretation tests not only quantitative skills but also relative, comparative, 
and analytical abilities. With practice and familiarity with different data 
representations, questions based on tables and graphs can be answered 
efficiently.
Graphical Representation
Definition
A graphic representation of data is 
one of the important ways of 
analysing numerical data. It presents 
statistical data in the form of lines or 
curves drawn across coordinated 
points.
Benefits
Graphs are easy to understand and 
visually appealing. They help study 
cause-effect relationships between 
variables and measure the extent of 
change when one variable changes 
by a certain amount.
Applications
They enable the study of both time 
series and frequency distribution, 
providing a clear account and 
precise picture of a problem in an 
accessible format.
Graphical representation makes complex data more accessible and helps identify patterns and trends that might not be 
immediately obvious in raw numerical data.
Page 4


Sources, 
Acquisition & 
Classification of 
Data
Data Interpretation
What is Data 
Interpretation?
The act of organizing and 
interpreting data to extract 
meaningful information. It involves 
drawing conclusions from data 
presented numerically in tabular or 
graphical form.
Required Skills
Good knowledge of percentage, 
ratio, proportion, and average 
concepts. Familiarity with graphical 
representations like Venn 
diagrams, graphs, pie-charts, 
histograms, and polygons.
Data vs Statistics
Data are individual pieces of factual information recorded for analysis - the 
raw information. Statistics are the results of data analysis through 
interpretation and presentation.
Data interpretation tests not only quantitative skills but also relative, comparative, 
and analytical abilities. With practice and familiarity with different data 
representations, questions based on tables and graphs can be answered 
efficiently.
Graphical Representation
Definition
A graphic representation of data is 
one of the important ways of 
analysing numerical data. It presents 
statistical data in the form of lines or 
curves drawn across coordinated 
points.
Benefits
Graphs are easy to understand and 
visually appealing. They help study 
cause-effect relationships between 
variables and measure the extent of 
change when one variable changes 
by a certain amount.
Applications
They enable the study of both time 
series and frequency distribution, 
providing a clear account and 
precise picture of a problem in an 
accessible format.
Graphical representation makes complex data more accessible and helps identify patterns and trends that might not be 
immediately obvious in raw numerical data.
General Principles of Graphic Representation
1
Coordinate Axes
There are two perpendicular lines 
called coordinate axes - the vertical 
one is known as Y-axis and the 
horizontal one is called X-axis. The 
point where these two lines intersect 
is called the origin or point 'O'.
2
Positive and Negative 
Values
On the X-axis, distances right of the 
origin have positive value and 
distances left have negative value. 
On the Y-axis, distances above the 
origin have positive value and below 
have negative value.
3
Formats
According to NTA-NET syllabus, 
graphic representation of data 
includes bar charts, histograms, pie 
charts, table charts, and line charts, 
each serving different purposes in 
data visualization.
Page 5


Sources, 
Acquisition & 
Classification of 
Data
Data Interpretation
What is Data 
Interpretation?
The act of organizing and 
interpreting data to extract 
meaningful information. It involves 
drawing conclusions from data 
presented numerically in tabular or 
graphical form.
Required Skills
Good knowledge of percentage, 
ratio, proportion, and average 
concepts. Familiarity with graphical 
representations like Venn 
diagrams, graphs, pie-charts, 
histograms, and polygons.
Data vs Statistics
Data are individual pieces of factual information recorded for analysis - the 
raw information. Statistics are the results of data analysis through 
interpretation and presentation.
Data interpretation tests not only quantitative skills but also relative, comparative, 
and analytical abilities. With practice and familiarity with different data 
representations, questions based on tables and graphs can be answered 
efficiently.
Graphical Representation
Definition
A graphic representation of data is 
one of the important ways of 
analysing numerical data. It presents 
statistical data in the form of lines or 
curves drawn across coordinated 
points.
Benefits
Graphs are easy to understand and 
visually appealing. They help study 
cause-effect relationships between 
variables and measure the extent of 
change when one variable changes 
by a certain amount.
Applications
They enable the study of both time 
series and frequency distribution, 
providing a clear account and 
precise picture of a problem in an 
accessible format.
Graphical representation makes complex data more accessible and helps identify patterns and trends that might not be 
immediately obvious in raw numerical data.
General Principles of Graphic Representation
1
Coordinate Axes
There are two perpendicular lines 
called coordinate axes - the vertical 
one is known as Y-axis and the 
horizontal one is called X-axis. The 
point where these two lines intersect 
is called the origin or point 'O'.
2
Positive and Negative 
Values
On the X-axis, distances right of the 
origin have positive value and 
distances left have negative value. 
On the Y-axis, distances above the 
origin have positive value and below 
have negative value.
3
Formats
According to NTA-NET syllabus, 
graphic representation of data 
includes bar charts, histograms, pie 
charts, table charts, and line charts, 
each serving different purposes in 
data visualization.
Bar-Chart
Definition
Also known as a column graph or bar 
diagram, it's a pictorial representation of data 
shown as rectangles with equal spaces 
between them and equal width. The height or 
length of each bar corresponds to the 
frequency of a particular observation.
Comparison
Bar charts allow for easy comparison of 
different quantities or the same quantity at 
different times. Given quantities can be 
compared by the height or length of bars.
Data Type
In bar graphs, the data is discrete rather than 
continuous. This presentation format makes 
comparative evaluation easier and is 
graphically attractive.
Bar charts can be drawn both vertically or horizontally depending on whether we take the frequency along the vertical or horizontal axes 
respectively.