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![Page 1: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/1.jpg)
الرحمن الله الرحمن بسم الله بسمالرحيمالرحيم
![Page 2: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/2.jpg)
Dr. Laila Mohamed NofalProfessor of Biostatistics
High Institute of Public HealthUniversity of Alexandria
![Page 3: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/3.jpg)
• Attract the reader’s attention
A graph or diagram, provides an easily understood
picture of the data. A suitable diagram is easier to
grasp and leaves a more permanent impression of the
main features of the data
• To compare two or more distributions.
Graphical presentation is the use of a graph to show the
distribution of data.
![Page 4: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/4.jpg)
There are many varieties of graphs. The use of
a particular type depends on:
– Type of data (quantitative continuous or
discrete or qualitative)
– Type of table (simple or complex)
Graphical Presentation
![Page 5: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/5.jpg)
One quantitative variable & Time.
Time may be years, months, weeks, days,
hours…)
No frequency distribution.
May be one or more quantitative variables
by time.
![Page 6: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/6.jpg)
The Line Graph
• Example:
YearCrude Birth Rate Per 1000 Population
199750
199851
199953
200055
200152
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The Line Graph
Figure (1) Crude birth rate of Country X 1997-2001
![Page 8: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/8.jpg)
Figure (1) Crude birth rate of Country X 1997-2001
![Page 9: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/9.jpg)
36.332.8
13.912.3 11.2 10.9
14.514.916.1
23.024.927.130.231.4
0
5
10
15
20
25
30
35
40
1970 1975 1980 1985 1990 1995 2000
Time (years)
CBR/
1000
popula
tion
Developed Countries Developing Countries
The Line Graph
![Page 10: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/10.jpg)
• For quantitative continuous variables• S.F.D.T only
![Page 11: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/11.jpg)
• Example:
Age in YearsFrequency
0 - 4
5 - 10
10 – 18
15 – 8
20 - 246
Total46
Y (Frequency or %)
X (Variable)
![Page 12: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/12.jpg)
• Example:
Age in Years
Figure (2): Distribution of patients by age in Hospital X, 2011
![Page 13: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/13.jpg)
• Quantitative continuous variable
• SFDT or Complex FDT
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• SFDT
• Points are joined by straight line
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• Complex FDT
• Points are joined by straight line
![Page 16: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/16.jpg)
Distribution of a group of patients by ageDistribution of a group of patients by age
Age Age groupgroupFreq.Freq.
RelativeRelative
Freq.Freq.
(%)(%)
Mid-Point(abscissa)
20-20-6612.212.2(20+30)/2=25
30-30-181836.736.7(30+40)/2=35
40-40-111122.522.5(40+50)/2=45
50-50-111122.522.5(50+60)/2=55
60-6960-69336.16.1(60+70)/2=65
TotalTotal4949100.0%100.0%
![Page 17: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/17.jpg)
01
02
0
0 25 35 45 55 65
Class Mid-Point
Fre
qu
en
cy
01
02
0
0 25 35 45 55 65
Class Mid-Point
Fre
qu
en
cy
Distribution of a group of patients by Distribution of a group of patients by ageage
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• Example:
Age in YearsSexMid-point of interval
MalesFemales
20-3( 12%)2( 10%))20+30/(2=25
30-9( 36%)6( 30%)(30+40)/2=35
40- 7 (28%) 5( 25%))40+50/(2=45
50-4( 16%)3( 15%))50+60/(2=55
60-692( 8%)4( 20%)(60+70)/2=65
Total25 20
![Page 19: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/19.jpg)
Figure (3): Distribution of patients by age and sex in Hospital X, 2012
0
5
10
15
20
25
30
35
40
25 35 45 55 65Age
%Males Females
![Page 20: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/20.jpg)
• Quantitative continuous variable
• SFDT or Complex FDT
• Points are joined by a smooth curve
• The more the number of points (categories)
the more smooth will be the curve
![Page 21: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/21.jpg)
0
5
10
15
20
25
30
35
0 30 40 50 60 70 .
Age (years)
%
Distribution of malaria cases by age
![Page 22: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/22.jpg)
• Qualitative or quantitative discrete variables
• Simple or complex frequency table
![Page 23: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/23.jpg)
• Simple frequency table
![Page 24: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/24.jpg)
• Complex frequency table
![Page 25: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/25.jpg)
Exampl
e
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0
5
10
15
20
25
30
35
40
45
%
Single Married Divorced Widowed
Marital status
Distribution of a group of HIV cases by marital status
Bars should be of equal widths and inter bar spacing and differ only in
height
![Page 27: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/27.jpg)
Exampl
e
![Page 28: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/28.jpg)
0
10
20
30
40
50
%
Single Married Divorced Widowed
Marital statusDistribution of a group of HIV cases by marital
status and gender
Male
Female
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The Pie Chart
• This type of graph can be used with all types of variables in simple frequency distribution tables.
1. The pie is divided into a number of sectors equal to the number of categories in the table so that each sector will represent one
category from the table.2. The starting line for sub-division of the circle is usually taken as 12
o’clock radius.3. The sub-division of the pie is usually in a clockwise direction.
4. The angle of the sector representing a particular category can be determined as follows:
angle = Frequency of each category X 360 Total frequency
![Page 30: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/30.jpg)
The Pie Chart
• Angle for single = 20 x360 = 100⁰ 72• Angle for married = 30 x360 = 150⁰ 72• Angle for widowed= 10 x360 = 50⁰ 72• Angle for divorced= 20 x360 = 60⁰ 72• Total = 100+150+50+60= 360⁰
Marital StatusFrequency
Single20
Married30
Divorced10
Widowed12
Total72
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The Pie Chart
Figure (4): Distribution of patients by marital status in Hospital X, in the year 2012
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Pie ChartDistribution of patients according to their blood group and sex
Blood Blood GrouGrou
pp
SexSex
MaleMaleFemaleFemale
Freq.Freq.Rel. Rel.
Freq.Freq.
(%)(%)Freq.Freq.
Rel.Rel.
Freq.Freq.
(%)(%)
AA202027.827.8151525.925.9
BB303041.741.7181831.031.0
ABAB101013.913.9131322.422.4
OO121216.616.6121220.720.7
TotalTotal7272100.0100.05858100.0100.0
![Page 33: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/33.jpg)
Pie Chart
Distribution of patients according to their blood group and sex
O16.6%
AB13.9%
B41.7%
A27.8%
O20.7%
AB22.4% B
31.0%
A25.9%
Male Female
![Page 34: بسم الله الرحمن الرحيم Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria.](https://reader035.fdocuments.net/reader035/viewer/2022062801/56649e2b5503460f94b18f46/html5/thumbnails/34.jpg)
GraphsGraphsGraphsGraphs
QuantitativeQuantitativeDataData
QuantitativeQuantitativeDataData
SFDTSFDT
Freq. PolygonFreq. Polygon
Freq. PolygonFreq. Polygon
HistogramHistogram
QualitativeQualitativeDataData
QualitativeQualitativeDataData
Complex Complex SFDTSFDT
Bar ChartBar Chart
Pie ChartPie ChartBar ChartBar Chart
ComplexComplex
ContinuousContinuousDiscreteDiscrete
Bar ChartBar Chart
DiscreteDiscreteContinuousContinuous
Bar ChartBar Chart
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