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Prof M A Hafez
Prof. & Advisor
Department of Biostatistics
Bangladesh University of Health Sciences (BUHS)
At the end of the session you should be able to:
 State importance of data presentation
 State different techniques of data Presentation;
 Prepare univariate and bivariate tables;
 Prepare appropriate graphs for:
- qualitative data
- quantitative data;
 Data collected and presented as it is, are called RAW data;
 These unsorted, unordered or untreated raw data fails to show
variations, patterns or the inherent message in the data set;
 Therefore, data need to be organized and presented in such a
way that they show patterns of variation clearly without loosing
any information of interest;
 Accurate methods of analysis can be decided upon only when
the characteristics of the data set are understood;
Frequency:
Frequency is the number of times an object, event
or characteristic occur;
Frequency distribution:
It is the organizing of a collection of observational/
numerical raw data into categories.
 Array
 Tabular
 Graphical
Array
Arranging in order
Family size: 4 6 8 2 9
Ascending: From lowest to highest
2 4 6 8 9
Descending: From highest to lowest
9 8 6 4 2
Method of summarizing data in rows and
columns :
into compact, concise and readily
understandable form.
without loosing any information of interest.
Presenting
 Univariate: one variable at a time.
 Bivariate: two variables at the same time.
 Multivariate: >2 variables at a time.
TYPES OF TABULAR PRESENTATION
 Suppose we have data of 20 adults aged from 20
to 49 years. There are 12 male and 8 female.
Table1 Gender distribution of 20 adults
Gender Number %
Male 12 60
Female 8 40
Total 20 100
Table 2 Age distribution of 20 adults
Age group
(yrs)
Number %
20-29 8 40
30-39 7 35
40-49 5 25
Total 20 100
Table 3 Gender distribution of 20 adults by age
group
Age group Male Female
20-29 5 3
30-39 5 2
40-49 2 3
Total 12 8
Advantages of tables
 A table helps organize information so it is easier to see
patterns and relationships.
 If a variable is continuous the table reveals a lot more
information.
 It may show the range, interval, and number of readings.
Why we use Graphical presentation ?
 Comprehension- Easy
 Visual presentation- Attractive
 Communication power - High
Data type
Table type
Univariate Bivariate
Qualitative • Simple Bar
• Component Bar
(Also called Proportional
Bar/Stack, Hundred percent bar)
• Pie diagram
• Line graph
Multiple Bar
Quantitative • Histogram
• Frequency Polygon
• Frequency Curve
• Ogive (Cumulative Frequency curve)
• Stem and leaf
• Box and whisker
Scattered
Diagram
 Used to present discrete or qualitative data.
 It includes separated bars of equal distance
across.
 The classification/categories of the variables are
usually placed on the X-axis and
 Y-axis usually represents the corresponding
frequency.
Table 4 percentage distribution of marking on tube-
well by level of arsenic (n=9,187 house holds)
*PPb = Parts Per billion
Figure 2 level of Arsenic in red, green and not marked
tube-well [Multiple bar chart]
Marki
ng on
tube-
well
Level of Arsenic
(PPb)*
Total
<50 50
% (n) % (n)
Red
45.2
(278)
54.8
(336)
100.0
(614)
Green
94.0
(2784)
6.0
(178)
100.0
(2962)
Not
marked
93.6
(5252)
6.4
(359)
100.0
(5611)
Total
90.5
(8314)
9.5
(873)
100.0
(9187)
0
10
20
30
40
50
60
70
80
90
100
Red Green Not marked
Percentage
Marking on tubewell
<50 >50
Table 5 EPI coverage survey on slums
of Dhaka
Figure 3 Percentage of EPI coverage survey
on slums of Dhaka [Proportional bar
chart/Hundred percent bar chart]
EPI coverage
Numb
er
Percent
age
Immunized 100 47
Partially
immunized
64 30
Not
immunized
49 23
Total 212 100 0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1
Not immunized
Partially immunized
Immunized
 It is commonly used graphical diagram for
presenting qualitative data.
 Shows the breakdown of a group or total in a
radius from.
Steps……
 1. draw a circle;
 2. divide the circle into sub– sets of the data corresponding
degrees of angle;
 3. compute the degree using formula:
degree=360*f/n
(f=freq. of a particular category, n = total frequency);
 The sectors are coloured or shaded in a different way.
Table 6 Distribution of patients visiting in
different diabetic hospital of Dhaka city in
a week
Figure 4 Distribution of patients visiting in
a week in different diabetic hospitals of
Dhaka city [Pie diagram]
Hospi
tal
A B C D Total
No of
patien
ts
1500 3660 1890 2575 9625
% of
patien
ts
16.0 37.0 20.0 27.0 100
Angle
1500X3
60/962
5
=56.1
3660X
360/9
625
=136.
9
1890X
360/9
625
=70.7
2575X
360/9
625
=96.3
360
16%
37%
27%
20%
A
B
C
D
 A line graph is used to present change over
time i.e trend.
 Line graph needs:
- Labeled X and Y axes
- Equal Intervals
- Data displayed by points connected
into lines
TABLE 7 DISTRIBUTION OF BED-SIDE TEMPERATURE
OF A PATIENT
FIGURE 5 DISTRIBUTION OF BED-SIDE
TEMPERATURE OF A PATIENT
(LINE GRAPH)
Time Temperature
6.00 AM 990F
9.00 AM 1040F
12.00 Noon 1050F
15.00 PM 1020F
18.00 PM 1010F
21.00 PM 1000F 96
97
98
99
100
101
102
103
104
105
106
 Graphical representation of the frequency
distribution of a quantitative variable.
 The variable of interest is placed on the x axis.
 A rectangle is drawn above each class interval with
its height corresponding to the interval’s
frequency, relative frequency, or percent
frequency.
 Unlike a bar graph, a histogram has no natural
separation between rectangles of next classes.
Table 8 Number of married couples by
their duration of marriage (in years)
Figure 6 Number of married couples by
their duration of marriage (in years)
[Histogram]
Duration of
marriage
(years)
Number of
married
couples
4-6 2
6-8 13
8-10 16
10-12 7
12-14 5
2
4
6
8
10
12
14
16
18
Number
of
married
couple
4 6 8 10 12 14
2
4
6
8
10
12
14
16
18
Frequency
4 6 8 10 12 14
 An ogive is a graph of a cumulative frequency
distribution.
 It is obtained by plotting the cumulative frequencies of
a distribution against the upper class boundaries.
 The frequency of each class is plotted as a point.
 The plotted points are connected by directly lines.
Cost (Tk) Percent Frequency Cumulative frequency
50-60 4 4
60-70 26 30
70-80 32 62
80-90 14 76
90-100 14 90
100-110 10 100
Total 100
Figure 8 Ogive with Cumulative Percent Frequencies
Food Cost (Tk)
20
40
60
80
100
Cumulative
Percent
Frequency
50 60 70 80 90 100 110
It shows correlation between two
quantitative variables
TABLE 10 MONTHLY FAMILY INCOME AND WEIGHT OF
CHILDREN AGED 5 YEARS AND ABOVE
Monthly Family income
(Taka )
Weight (kg)
13000 15.5
20000 19.8
34500 21.5
24500 16.8
15500 12.6
30000 16.6
13000 18.1
8000 13.1
24500 20.1
0
5
10
15
20
25
0 50 100 150 200 250 300 350 400
Monthly family income Taka ‘00
FIGURE 9 MONTHLY FAMILY INCOME AND WEIGHT OF CHILDREN 5
YEARS AND ABOVE [SCATTER DIAGRAM]
Importance of graphs
 They are attractive and impressive
 save time
 make data simple
 make comparison easy
Data presentation

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Data presentation

  • 1. Prof M A Hafez Prof. & Advisor Department of Biostatistics Bangladesh University of Health Sciences (BUHS)
  • 2. At the end of the session you should be able to:  State importance of data presentation  State different techniques of data Presentation;  Prepare univariate and bivariate tables;  Prepare appropriate graphs for: - qualitative data - quantitative data;
  • 3.  Data collected and presented as it is, are called RAW data;  These unsorted, unordered or untreated raw data fails to show variations, patterns or the inherent message in the data set;  Therefore, data need to be organized and presented in such a way that they show patterns of variation clearly without loosing any information of interest;  Accurate methods of analysis can be decided upon only when the characteristics of the data set are understood;
  • 4. Frequency: Frequency is the number of times an object, event or characteristic occur; Frequency distribution: It is the organizing of a collection of observational/ numerical raw data into categories.
  • 5.  Array  Tabular  Graphical Array Arranging in order Family size: 4 6 8 2 9 Ascending: From lowest to highest 2 4 6 8 9 Descending: From highest to lowest 9 8 6 4 2
  • 6. Method of summarizing data in rows and columns : into compact, concise and readily understandable form. without loosing any information of interest.
  • 7. Presenting  Univariate: one variable at a time.  Bivariate: two variables at the same time.  Multivariate: >2 variables at a time. TYPES OF TABULAR PRESENTATION
  • 8.  Suppose we have data of 20 adults aged from 20 to 49 years. There are 12 male and 8 female.
  • 9. Table1 Gender distribution of 20 adults Gender Number % Male 12 60 Female 8 40 Total 20 100
  • 10. Table 2 Age distribution of 20 adults Age group (yrs) Number % 20-29 8 40 30-39 7 35 40-49 5 25 Total 20 100
  • 11. Table 3 Gender distribution of 20 adults by age group Age group Male Female 20-29 5 3 30-39 5 2 40-49 2 3 Total 12 8
  • 12. Advantages of tables  A table helps organize information so it is easier to see patterns and relationships.  If a variable is continuous the table reveals a lot more information.  It may show the range, interval, and number of readings.
  • 13. Why we use Graphical presentation ?  Comprehension- Easy  Visual presentation- Attractive  Communication power - High
  • 14. Data type Table type Univariate Bivariate Qualitative • Simple Bar • Component Bar (Also called Proportional Bar/Stack, Hundred percent bar) • Pie diagram • Line graph Multiple Bar Quantitative • Histogram • Frequency Polygon • Frequency Curve • Ogive (Cumulative Frequency curve) • Stem and leaf • Box and whisker Scattered Diagram
  • 15.  Used to present discrete or qualitative data.  It includes separated bars of equal distance across.  The classification/categories of the variables are usually placed on the X-axis and  Y-axis usually represents the corresponding frequency.
  • 16.
  • 17. Table 4 percentage distribution of marking on tube- well by level of arsenic (n=9,187 house holds) *PPb = Parts Per billion Figure 2 level of Arsenic in red, green and not marked tube-well [Multiple bar chart] Marki ng on tube- well Level of Arsenic (PPb)* Total <50 50 % (n) % (n) Red 45.2 (278) 54.8 (336) 100.0 (614) Green 94.0 (2784) 6.0 (178) 100.0 (2962) Not marked 93.6 (5252) 6.4 (359) 100.0 (5611) Total 90.5 (8314) 9.5 (873) 100.0 (9187) 0 10 20 30 40 50 60 70 80 90 100 Red Green Not marked Percentage Marking on tubewell <50 >50
  • 18. Table 5 EPI coverage survey on slums of Dhaka Figure 3 Percentage of EPI coverage survey on slums of Dhaka [Proportional bar chart/Hundred percent bar chart] EPI coverage Numb er Percent age Immunized 100 47 Partially immunized 64 30 Not immunized 49 23 Total 212 100 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 1 Not immunized Partially immunized Immunized
  • 19.  It is commonly used graphical diagram for presenting qualitative data.  Shows the breakdown of a group or total in a radius from.
  • 20. Steps……  1. draw a circle;  2. divide the circle into sub– sets of the data corresponding degrees of angle;  3. compute the degree using formula: degree=360*f/n (f=freq. of a particular category, n = total frequency);  The sectors are coloured or shaded in a different way.
  • 21. Table 6 Distribution of patients visiting in different diabetic hospital of Dhaka city in a week Figure 4 Distribution of patients visiting in a week in different diabetic hospitals of Dhaka city [Pie diagram] Hospi tal A B C D Total No of patien ts 1500 3660 1890 2575 9625 % of patien ts 16.0 37.0 20.0 27.0 100 Angle 1500X3 60/962 5 =56.1 3660X 360/9 625 =136. 9 1890X 360/9 625 =70.7 2575X 360/9 625 =96.3 360 16% 37% 27% 20% A B C D
  • 22.  A line graph is used to present change over time i.e trend.  Line graph needs: - Labeled X and Y axes - Equal Intervals - Data displayed by points connected into lines
  • 23. TABLE 7 DISTRIBUTION OF BED-SIDE TEMPERATURE OF A PATIENT FIGURE 5 DISTRIBUTION OF BED-SIDE TEMPERATURE OF A PATIENT (LINE GRAPH) Time Temperature 6.00 AM 990F 9.00 AM 1040F 12.00 Noon 1050F 15.00 PM 1020F 18.00 PM 1010F 21.00 PM 1000F 96 97 98 99 100 101 102 103 104 105 106
  • 24.  Graphical representation of the frequency distribution of a quantitative variable.  The variable of interest is placed on the x axis.  A rectangle is drawn above each class interval with its height corresponding to the interval’s frequency, relative frequency, or percent frequency.  Unlike a bar graph, a histogram has no natural separation between rectangles of next classes.
  • 25. Table 8 Number of married couples by their duration of marriage (in years) Figure 6 Number of married couples by their duration of marriage (in years) [Histogram] Duration of marriage (years) Number of married couples 4-6 2 6-8 13 8-10 16 10-12 7 12-14 5 2 4 6 8 10 12 14 16 18 Number of married couple 4 6 8 10 12 14
  • 27.  An ogive is a graph of a cumulative frequency distribution.  It is obtained by plotting the cumulative frequencies of a distribution against the upper class boundaries.  The frequency of each class is plotted as a point.  The plotted points are connected by directly lines.
  • 28. Cost (Tk) Percent Frequency Cumulative frequency 50-60 4 4 60-70 26 30 70-80 32 62 80-90 14 76 90-100 14 90 100-110 10 100 Total 100
  • 29. Figure 8 Ogive with Cumulative Percent Frequencies Food Cost (Tk) 20 40 60 80 100 Cumulative Percent Frequency 50 60 70 80 90 100 110
  • 30. It shows correlation between two quantitative variables
  • 31. TABLE 10 MONTHLY FAMILY INCOME AND WEIGHT OF CHILDREN AGED 5 YEARS AND ABOVE Monthly Family income (Taka ) Weight (kg) 13000 15.5 20000 19.8 34500 21.5 24500 16.8 15500 12.6 30000 16.6 13000 18.1 8000 13.1 24500 20.1
  • 32. 0 5 10 15 20 25 0 50 100 150 200 250 300 350 400 Monthly family income Taka ‘00 FIGURE 9 MONTHLY FAMILY INCOME AND WEIGHT OF CHILDREN 5 YEARS AND ABOVE [SCATTER DIAGRAM]
  • 33. Importance of graphs  They are attractive and impressive  save time  make data simple  make comparison easy