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Presentation of Data
1. INTRODUCTION
You have already learnt in previous
chapters how data are collected and
organised. As data are generally
voluminous, they need to be put in a
compact and presentable form. This
chapter deals with presentation of data
precisely so that the voluminous data
collected could be made usable readily
and are easily comprehended. There are
generally three forms of presentation of
data:
• Textual or Descriptive presentation
• Tabular presentation
• Diagrammatic presentation.
2. TEXTUAL PRESENTATION OF DATA
In textual presentation, data are
described within the text. When the
quantity of data is not too large this form
of presentation is more suitable. Look
at the following cases:
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.
Studying this chapter should
enable you to:
• present data using tables;
• represent data using appropriate
diagrams.
CHAPTER
2024-25
Page 2


Presentation of Data
1. INTRODUCTION
You have already learnt in previous
chapters how data are collected and
organised. As data are generally
voluminous, they need to be put in a
compact and presentable form. This
chapter deals with presentation of data
precisely so that the voluminous data
collected could be made usable readily
and are easily comprehended. There are
generally three forms of presentation of
data:
• Textual or Descriptive presentation
• Tabular presentation
• Diagrammatic presentation.
2. TEXTUAL PRESENTATION OF DATA
In textual presentation, data are
described within the text. When the
quantity of data is not too large this form
of presentation is more suitable. Look
at the following cases:
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.
Studying this chapter should
enable you to:
• present data using tables;
• represent data using appropriate
diagrams.
CHAPTER
2024-25
PRESENTATION OF DATA 41
Case 2
Census of India 2001 reported that
Indian population had risen to 102 crore
of which only 49 crore were females
against 53 crore males. Seventy-four
crore people resided in rural India and
only 28 crore lived in towns or cities.
While there were 62 crore non-worker
population against 40 crore workers in
the entire country. Urban population had
an even higher share of non-workers (19
crore) against workers (9 crore) as
compared to the rural population where
there were 31 crore workers out of a 74
crore population...
In both the cases data have been
presented only in the text. A serious
drawback of this method of presentation
is that one has to go through the
complete text of presentation for
comprehension. But, it is also true that
this matter often enables one to
emphasise certain points of the
presentation.
and columns (read vertically). For
example see Table 4.1 tabulating
information about literacy rates. It has
three rows (for male, female and total)
and three columns (for urban, rural
and total). It is called a 3 × 3 Table giving
9 items of information in 9 boxes called
the "cells" of the Table. Each cell gives
information that relates an attribute of
gender ("male", "female" or total) with a
number (literacy percentages of rural
people, urban people and total). The
most important advantage of tabulation
is that it organises data for further
statistical treatment and decision-
making. Classification used in
tabulation is of four kinds:
• Qualitative
• Quantitative
• Temporal and
• Spatial
Qualitative classification
When classification is done according
to attributes, such as social status,
physical status, nationality, etc., it is
called qualitative classification. For
example, in Table 4.1 the attributes for
classification are sex and location which
are qualitative in nature.
TABLE 4.1
Literacy in India by sex and location (per cent)
Location Total
Sex Rural Urban
Male 79 90 82
Female 59 80 65
Total 68 84 74
Source: Census of India 2011. (Literacy rates
relate to population aged 7 years and above)
3. TABULAR PRESENTATION OF DATA
In a tabular presentation, data are
presented in rows (read horizontally)
2024-25
Page 3


Presentation of Data
1. INTRODUCTION
You have already learnt in previous
chapters how data are collected and
organised. As data are generally
voluminous, they need to be put in a
compact and presentable form. This
chapter deals with presentation of data
precisely so that the voluminous data
collected could be made usable readily
and are easily comprehended. There are
generally three forms of presentation of
data:
• Textual or Descriptive presentation
• Tabular presentation
• Diagrammatic presentation.
2. TEXTUAL PRESENTATION OF DATA
In textual presentation, data are
described within the text. When the
quantity of data is not too large this form
of presentation is more suitable. Look
at the following cases:
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.
Studying this chapter should
enable you to:
• present data using tables;
• represent data using appropriate
diagrams.
CHAPTER
2024-25
PRESENTATION OF DATA 41
Case 2
Census of India 2001 reported that
Indian population had risen to 102 crore
of which only 49 crore were females
against 53 crore males. Seventy-four
crore people resided in rural India and
only 28 crore lived in towns or cities.
While there were 62 crore non-worker
population against 40 crore workers in
the entire country. Urban population had
an even higher share of non-workers (19
crore) against workers (9 crore) as
compared to the rural population where
there were 31 crore workers out of a 74
crore population...
In both the cases data have been
presented only in the text. A serious
drawback of this method of presentation
is that one has to go through the
complete text of presentation for
comprehension. But, it is also true that
this matter often enables one to
emphasise certain points of the
presentation.
and columns (read vertically). For
example see Table 4.1 tabulating
information about literacy rates. It has
three rows (for male, female and total)
and three columns (for urban, rural
and total). It is called a 3 × 3 Table giving
9 items of information in 9 boxes called
the "cells" of the Table. Each cell gives
information that relates an attribute of
gender ("male", "female" or total) with a
number (literacy percentages of rural
people, urban people and total). The
most important advantage of tabulation
is that it organises data for further
statistical treatment and decision-
making. Classification used in
tabulation is of four kinds:
• Qualitative
• Quantitative
• Temporal and
• Spatial
Qualitative classification
When classification is done according
to attributes, such as social status,
physical status, nationality, etc., it is
called qualitative classification. For
example, in Table 4.1 the attributes for
classification are sex and location which
are qualitative in nature.
TABLE 4.1
Literacy in India by sex and location (per cent)
Location Total
Sex Rural Urban
Male 79 90 82
Female 59 80 65
Total 68 84 74
Source: Census of India 2011. (Literacy rates
relate to population aged 7 years and above)
3. TABULAR PRESENTATION OF DATA
In a tabular presentation, data are
presented in rows (read horizontally)
2024-25
42 STATISTICS FOR ECONOMICS
Quantitative classification
In quantitative classification, the data
are classified on the basis of
characteristics which are quantitative in
nature. In other words these
characteristics can be measured
quantitatively. For example, age, height,
production, income, etc are quantitative
characteristics. Classes are formed by
assigning limits called class limits for the
values of the characteristic under
consideration. An example of quantit-
ative classification is given in Table 4.2.
Calculate the missing figures in the Table.
TABLE 4.2
Distribution of 542 respondents by
their age in an election study in Bihar
Age group No. of
(yrs) respondents Per cent
20–30 3 0.55
30–40 61 11.25
40–50 132 24.35
50–60 153 28.24
60–70 ? ?
70–80 51 9.41
80–90 2 0.37
All ? 100.00
Source: Assembly election Patna central
constituency 2005, A.N. Sinha Institute of Social
Studies, Patna.
Here classifying characteristic is age
in years and is quantifiable.
Activities
• Discuss how the total values
are arrived at in Table 4.1
• Construct a table presenting
data on preferential liking of the
students of your class for Star
News, Zee News, BBC World,
CNN, Aaj Tak and DD News.
• Prepare a table of
(i) heights (in cm) and
(ii) weights (in kg) of students
of your class.
Temporal classification
In this classification time becomes the
classifying variable and data are
categorised according to time. Time
may be in hours, days, weeks, months,
years, etc. For example, see Table 4.3.
TABLE 4.3
Yearly sales of a tea shop
from 1995 to 2000
Years Sale (Rs in lakhs)
1995 79.2
1996 81.3
1997 82.4
1998 80.5
1999 100.2
2000 91.2
Data Source: Unpublished data.
In this table the classifying
characteristic is sales in a year and
takes values in the scale of time.
Activity
• Go to your school office and
collect data on the number of
students studied in the school in
each class for the last ten years
and present the data in a table.
Spatial classification
When classification is done on the basis
of place, it is called spatial
classification. The place may be a
village/town, block, district, state,
country, etc.
Table 4.4 is an example of spatial
classification.
2024-25
Page 4


Presentation of Data
1. INTRODUCTION
You have already learnt in previous
chapters how data are collected and
organised. As data are generally
voluminous, they need to be put in a
compact and presentable form. This
chapter deals with presentation of data
precisely so that the voluminous data
collected could be made usable readily
and are easily comprehended. There are
generally three forms of presentation of
data:
• Textual or Descriptive presentation
• Tabular presentation
• Diagrammatic presentation.
2. TEXTUAL PRESENTATION OF DATA
In textual presentation, data are
described within the text. When the
quantity of data is not too large this form
of presentation is more suitable. Look
at the following cases:
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.
Studying this chapter should
enable you to:
• present data using tables;
• represent data using appropriate
diagrams.
CHAPTER
2024-25
PRESENTATION OF DATA 41
Case 2
Census of India 2001 reported that
Indian population had risen to 102 crore
of which only 49 crore were females
against 53 crore males. Seventy-four
crore people resided in rural India and
only 28 crore lived in towns or cities.
While there were 62 crore non-worker
population against 40 crore workers in
the entire country. Urban population had
an even higher share of non-workers (19
crore) against workers (9 crore) as
compared to the rural population where
there were 31 crore workers out of a 74
crore population...
In both the cases data have been
presented only in the text. A serious
drawback of this method of presentation
is that one has to go through the
complete text of presentation for
comprehension. But, it is also true that
this matter often enables one to
emphasise certain points of the
presentation.
and columns (read vertically). For
example see Table 4.1 tabulating
information about literacy rates. It has
three rows (for male, female and total)
and three columns (for urban, rural
and total). It is called a 3 × 3 Table giving
9 items of information in 9 boxes called
the "cells" of the Table. Each cell gives
information that relates an attribute of
gender ("male", "female" or total) with a
number (literacy percentages of rural
people, urban people and total). The
most important advantage of tabulation
is that it organises data for further
statistical treatment and decision-
making. Classification used in
tabulation is of four kinds:
• Qualitative
• Quantitative
• Temporal and
• Spatial
Qualitative classification
When classification is done according
to attributes, such as social status,
physical status, nationality, etc., it is
called qualitative classification. For
example, in Table 4.1 the attributes for
classification are sex and location which
are qualitative in nature.
TABLE 4.1
Literacy in India by sex and location (per cent)
Location Total
Sex Rural Urban
Male 79 90 82
Female 59 80 65
Total 68 84 74
Source: Census of India 2011. (Literacy rates
relate to population aged 7 years and above)
3. TABULAR PRESENTATION OF DATA
In a tabular presentation, data are
presented in rows (read horizontally)
2024-25
42 STATISTICS FOR ECONOMICS
Quantitative classification
In quantitative classification, the data
are classified on the basis of
characteristics which are quantitative in
nature. In other words these
characteristics can be measured
quantitatively. For example, age, height,
production, income, etc are quantitative
characteristics. Classes are formed by
assigning limits called class limits for the
values of the characteristic under
consideration. An example of quantit-
ative classification is given in Table 4.2.
Calculate the missing figures in the Table.
TABLE 4.2
Distribution of 542 respondents by
their age in an election study in Bihar
Age group No. of
(yrs) respondents Per cent
20–30 3 0.55
30–40 61 11.25
40–50 132 24.35
50–60 153 28.24
60–70 ? ?
70–80 51 9.41
80–90 2 0.37
All ? 100.00
Source: Assembly election Patna central
constituency 2005, A.N. Sinha Institute of Social
Studies, Patna.
Here classifying characteristic is age
in years and is quantifiable.
Activities
• Discuss how the total values
are arrived at in Table 4.1
• Construct a table presenting
data on preferential liking of the
students of your class for Star
News, Zee News, BBC World,
CNN, Aaj Tak and DD News.
• Prepare a table of
(i) heights (in cm) and
(ii) weights (in kg) of students
of your class.
Temporal classification
In this classification time becomes the
classifying variable and data are
categorised according to time. Time
may be in hours, days, weeks, months,
years, etc. For example, see Table 4.3.
TABLE 4.3
Yearly sales of a tea shop
from 1995 to 2000
Years Sale (Rs in lakhs)
1995 79.2
1996 81.3
1997 82.4
1998 80.5
1999 100.2
2000 91.2
Data Source: Unpublished data.
In this table the classifying
characteristic is sales in a year and
takes values in the scale of time.
Activity
• Go to your school office and
collect data on the number of
students studied in the school in
each class for the last ten years
and present the data in a table.
Spatial classification
When classification is done on the basis
of place, it is called spatial
classification. The place may be a
village/town, block, district, state,
country, etc.
Table 4.4 is an example of spatial
classification.
2024-25
PRESENTATION OF DATA 43
TABLE 4.4
Export from India to rest of the world in
2013-14 as share of total export (per cent)
Destination Export share
USA 12.5
Germany 2.4
Other EU 10.9
UK 3.1
Japan 2.2
Russia 0.7
China 4.7
West Asia -Gulf Coop. Council 15.3
Other Asia 29.4
Others 18.8
All 100.0
(Total Exports: US $ 314.40 billion)
Activity
• Construct a table presenting
data collected from students of
your class according to their
native states/residential
locality.
4.TABULATION OF DATA AND PARTS
OF A TABLE
To construct a table it is important to
learn first what are the parts of a good
statistical table. When put together
systematically these parts form a table.
The most simple way of conceptualising
a table is to present the data in rows
and columns alongwith some
explanatory notes. Tabulation can be
done using one-way, two-way or three-
way classification depending upon the
number of characteristics involved. A
good table should essentially have the
following:
(i) Table Number
Table number is assigned to a table for
identification purpose. If more than one
table is presented, it is the table
number that distinguishes one table
from another. It is given at the top or
at the beginning of the title of the table.
Generally, table numbers are whole
numbers in ascending order if there are
many tables in a book. Subscripted
numbers, like 1.2, 3.1, etc., are also
used for identifying the table according
to its location. For example, Table 4.5
should be read as the fifth table of the
fourth chapter, and so on
(See Table  4.5).
(ii) Title
The title of a table narrates about the
contents of the table. It has to be  clear,
brief and carefully worded so that the
interpretations made from the table are
clear and free from  ambiguity. It finds
place at the head of the table
succeeding the table number or just
below it (See Table 4.5).
(iii) Captions or Column Headings
At the top of each column in a table a
column designation is given to explain
figures of the column. This is
called caption or column heading
(See Table 4.5).
(iv) Stubs or Row Headings
Like a caption or column heading, each
row of the table has to be given a
heading. The designations of the rows
are also called stubs or stub items, and
the complete left column is known as
2024-25
Page 5


Presentation of Data
1. INTRODUCTION
You have already learnt in previous
chapters how data are collected and
organised. As data are generally
voluminous, they need to be put in a
compact and presentable form. This
chapter deals with presentation of data
precisely so that the voluminous data
collected could be made usable readily
and are easily comprehended. There are
generally three forms of presentation of
data:
• Textual or Descriptive presentation
• Tabular presentation
• Diagrammatic presentation.
2. TEXTUAL PRESENTATION OF DATA
In textual presentation, data are
described within the text. When the
quantity of data is not too large this form
of presentation is more suitable. Look
at the following cases:
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.
Studying this chapter should
enable you to:
• present data using tables;
• represent data using appropriate
diagrams.
CHAPTER
2024-25
PRESENTATION OF DATA 41
Case 2
Census of India 2001 reported that
Indian population had risen to 102 crore
of which only 49 crore were females
against 53 crore males. Seventy-four
crore people resided in rural India and
only 28 crore lived in towns or cities.
While there were 62 crore non-worker
population against 40 crore workers in
the entire country. Urban population had
an even higher share of non-workers (19
crore) against workers (9 crore) as
compared to the rural population where
there were 31 crore workers out of a 74
crore population...
In both the cases data have been
presented only in the text. A serious
drawback of this method of presentation
is that one has to go through the
complete text of presentation for
comprehension. But, it is also true that
this matter often enables one to
emphasise certain points of the
presentation.
and columns (read vertically). For
example see Table 4.1 tabulating
information about literacy rates. It has
three rows (for male, female and total)
and three columns (for urban, rural
and total). It is called a 3 × 3 Table giving
9 items of information in 9 boxes called
the "cells" of the Table. Each cell gives
information that relates an attribute of
gender ("male", "female" or total) with a
number (literacy percentages of rural
people, urban people and total). The
most important advantage of tabulation
is that it organises data for further
statistical treatment and decision-
making. Classification used in
tabulation is of four kinds:
• Qualitative
• Quantitative
• Temporal and
• Spatial
Qualitative classification
When classification is done according
to attributes, such as social status,
physical status, nationality, etc., it is
called qualitative classification. For
example, in Table 4.1 the attributes for
classification are sex and location which
are qualitative in nature.
TABLE 4.1
Literacy in India by sex and location (per cent)
Location Total
Sex Rural Urban
Male 79 90 82
Female 59 80 65
Total 68 84 74
Source: Census of India 2011. (Literacy rates
relate to population aged 7 years and above)
3. TABULAR PRESENTATION OF DATA
In a tabular presentation, data are
presented in rows (read horizontally)
2024-25
42 STATISTICS FOR ECONOMICS
Quantitative classification
In quantitative classification, the data
are classified on the basis of
characteristics which are quantitative in
nature. In other words these
characteristics can be measured
quantitatively. For example, age, height,
production, income, etc are quantitative
characteristics. Classes are formed by
assigning limits called class limits for the
values of the characteristic under
consideration. An example of quantit-
ative classification is given in Table 4.2.
Calculate the missing figures in the Table.
TABLE 4.2
Distribution of 542 respondents by
their age in an election study in Bihar
Age group No. of
(yrs) respondents Per cent
20–30 3 0.55
30–40 61 11.25
40–50 132 24.35
50–60 153 28.24
60–70 ? ?
70–80 51 9.41
80–90 2 0.37
All ? 100.00
Source: Assembly election Patna central
constituency 2005, A.N. Sinha Institute of Social
Studies, Patna.
Here classifying characteristic is age
in years and is quantifiable.
Activities
• Discuss how the total values
are arrived at in Table 4.1
• Construct a table presenting
data on preferential liking of the
students of your class for Star
News, Zee News, BBC World,
CNN, Aaj Tak and DD News.
• Prepare a table of
(i) heights (in cm) and
(ii) weights (in kg) of students
of your class.
Temporal classification
In this classification time becomes the
classifying variable and data are
categorised according to time. Time
may be in hours, days, weeks, months,
years, etc. For example, see Table 4.3.
TABLE 4.3
Yearly sales of a tea shop
from 1995 to 2000
Years Sale (Rs in lakhs)
1995 79.2
1996 81.3
1997 82.4
1998 80.5
1999 100.2
2000 91.2
Data Source: Unpublished data.
In this table the classifying
characteristic is sales in a year and
takes values in the scale of time.
Activity
• Go to your school office and
collect data on the number of
students studied in the school in
each class for the last ten years
and present the data in a table.
Spatial classification
When classification is done on the basis
of place, it is called spatial
classification. The place may be a
village/town, block, district, state,
country, etc.
Table 4.4 is an example of spatial
classification.
2024-25
PRESENTATION OF DATA 43
TABLE 4.4
Export from India to rest of the world in
2013-14 as share of total export (per cent)
Destination Export share
USA 12.5
Germany 2.4
Other EU 10.9
UK 3.1
Japan 2.2
Russia 0.7
China 4.7
West Asia -Gulf Coop. Council 15.3
Other Asia 29.4
Others 18.8
All 100.0
(Total Exports: US $ 314.40 billion)
Activity
• Construct a table presenting
data collected from students of
your class according to their
native states/residential
locality.
4.TABULATION OF DATA AND PARTS
OF A TABLE
To construct a table it is important to
learn first what are the parts of a good
statistical table. When put together
systematically these parts form a table.
The most simple way of conceptualising
a table is to present the data in rows
and columns alongwith some
explanatory notes. Tabulation can be
done using one-way, two-way or three-
way classification depending upon the
number of characteristics involved. A
good table should essentially have the
following:
(i) Table Number
Table number is assigned to a table for
identification purpose. If more than one
table is presented, it is the table
number that distinguishes one table
from another. It is given at the top or
at the beginning of the title of the table.
Generally, table numbers are whole
numbers in ascending order if there are
many tables in a book. Subscripted
numbers, like 1.2, 3.1, etc., are also
used for identifying the table according
to its location. For example, Table 4.5
should be read as the fifth table of the
fourth chapter, and so on
(See Table  4.5).
(ii) Title
The title of a table narrates about the
contents of the table. It has to be  clear,
brief and carefully worded so that the
interpretations made from the table are
clear and free from  ambiguity. It finds
place at the head of the table
succeeding the table number or just
below it (See Table 4.5).
(iii) Captions or Column Headings
At the top of each column in a table a
column designation is given to explain
figures of the column. This is
called caption or column heading
(See Table 4.5).
(iv) Stubs or Row Headings
Like a caption or column heading, each
row of the table has to be given a
heading. The designations of the rows
are also called stubs or stub items, and
the complete left column is known as
2024-25
44 STATISTICS FOR ECONOMICS
stub column. A brief description of the
row headings may also be given at the
left hand top in the table. (See Table
4.5).
(v) Body of the Table
Body of a table is the main part and it
contains the actual data. Location of
any one figure/data in the table is
fixed and determined by the row and
column of the table.  For example, data
in the second row and fourth column
indicate that 25 crore females in rural
India were non-workers in 2001 (See
Table 4.5).
(vi) Unit of Measurement
The unit of measurement of the
figures in the table (actual data)
should always be stated alongwith
the title. If different units are there
for rows or columns of the table,
these units must be stated
alongwith ‘stubs’ or ‘captions’. If
figures are large, they should
be rounded up and the method
(Note : Table 4.5 presents the same data in tabular form already presented through case 2 in
textual presentation of data)
Table 4.5  Population of India according to workers and non-workers by gender and location, 2001
Location Gender Workers Non-worker Total
Main Marginal Total
Male 17 3 20 18 38
Female 6 5 11 25 36
Total 23 8 31 43 74
Male 7 1 8 7 15
Female 1 0 1 12 13
Total 8 1 9 19 28
Male 24 4 28 25 53
Female 7 5 12 37 49
Total 31 9 40 62 102
Source : Census of India 2001
Note : Figures are rounded to nearest crore
All Urban Rural
Body of the table
?
Note
?
Source
?
Row Headings/stubs
?
?
Units
(Crore)
?
Column Headings/Captions
?
Title
?
Table Number
2024-25
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FAQs on NCERT Textbook - Presentation of Data - Economics Class 11 - Commerce

1. What is the importance of presenting data effectively?
Ans. Presenting data effectively is important because it helps in conveying information clearly and visually. It enhances understanding, enables better decision-making, and facilitates effective communication. By presenting data in a meaningful and organized manner, it becomes easier for the audience to interpret and analyze the information.
2. What are the different methods of presenting data?
Ans. There are various methods of presenting data, including tables, graphs, charts, diagrams, and maps. Tables are used to present numerical data in a structured format, while graphs and charts are used to represent numerical or categorical data visually. Diagrams, such as flowcharts or Venn diagrams, are useful for illustrating processes or relationships. Maps are employed to display geographical or spatial data.
3. How can data be represented using graphs?
Ans. Graphs are an effective way to represent data visually. Different types of graphs, such as bar graphs, line graphs, and pie charts, can be used depending on the nature of the data being presented. Bar graphs are ideal for comparing different categories or groups, while line graphs are suitable for showing trends over time. Pie charts are used to represent data as a percentage of a whole.
4. What are the steps involved in creating a good data presentation?
Ans. Creating a good data presentation involves several steps. First, it is important to identify the purpose of the presentation and the target audience. Then, the data needs to be collected, organized, and analyzed to derive meaningful insights. Selecting appropriate visual aids, such as graphs or charts, is crucial for effectively presenting the data. Finally, the presentation should be well-structured, with a clear title, labels, and a concise explanation of the data.
5. What are the common mistakes to avoid when presenting data?
Ans. When presenting data, it is essential to avoid common mistakes that can hinder effective communication. Some of these mistakes include overcrowding the presentation with excessive data, using complex or unclear visuals, not providing proper context or explanation for the data, and failing to consider the needs and knowledge of the audience. It is also important to double-check the accuracy of the data and ensure that it is presented in a logical and coherent manner.
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