SlideShare a Scribd company logo
‫الرحيم‬ ‫الرحمن‬ ‫هللا‬ ‫بسم‬
Introduction to
Biostatistics
Dr. Moataza Mahmoud Abdel Wahab
Lecturer of Biostatistics
High Institute of Public Health
University of Alexandria
Biostatistics
(a portmanteau word made from biology and
statistics)
The application of statistics to a wide range of topics
in biology.
Biostatistics
It is the science which deals with development and
application of the most appropriate methods for
the:
Collection of data.
Presentation of the collected data.
Analysis and interpretation of the results.
Making decisions on the basis of such analysis
Other definitions for “Statistics”
 Frequently used in referral to recorded data
 Denotes characteristics calculated for a set of data :
sample mean
Role of statisticians
 To guide the design of an experiment or survey
prior to data collection
 To analyze data using proper statistical
procedures and techniques
 To present and interpret the results to researchers
and other decision makers
Sources of
data
Records Surveys Experiments
Comprehensive Sample
Types of data
Constant
Variables
Quantitative
continuous
Types of variables
Quantitative variables Qualitative variables
Quantitative
descrete
Qualitative
nominal
Qualitative
ordinal
 Numerical presentation
 Graphical presentation
 Mathematical presentation
Methods of presentation of data
1- Numerical presentation
Tabular presentation (simple – complex)
Simple frequency distribution Table (S.F.D.T.)
Title
Name of variable
(Units of variable)
Frequency %
-
- Categories
-
Total
Table (I): Distribution of 50 patients at the surgical
department of Alexandria hospital in May 2008 according
to their ABO blood groups
Blood group Frequency %
A
B
AB
O
12
18
5
15
24
36
10
30
Total 50 100
Table (II): Distribution of 50 patients at the surgical
department of Alexandria hospital in May 2008 according
to their age
Age
(years)
Frequency %
20-<30
30-
40-
50+
12
18
5
15
24
36
10
30
Total 50 100
Complex frequency distribution Table
Table (III): Distribution of 20 lung cancer patients at the chest department
of Alexandria hospital and 40 controls in May 2008 according to smoking
Smoking
Lung cancer
Total
Cases Control
No. % No. % No. %
Smoker 15 75% 8 20% 23 38.33
Non
smoker 5 25% 32 80% 37 61.67
Total 20 100 40 100 60 100
Complex frequency distribution Table
Table (IV): Distribution of 60 patients at the chest department of
Alexandria hospital in May 2008 according to smoking & lung cancer
Smoking
Lung cancer
Total
positive negative
No. % No. % No. %
Smoker 15 65.2 8 34.8 23 100
Non
smoker 5 13.5 32 86.5 37 100
Total 20 33.3 40 66.7 60 100
2- Graphical presentation
 Graphs drawn using Cartesian
coordinates
• Line graph
• Frequency polygon
• Frequency curve
• Histogram
• Bar graph
• Scatter plot
 Pie chart
 Statistical maps
rules
Line Graph
0
10
20
30
40
50
60
1960 1970 1980 1990 2000
Year
MMR/1000 Year MMR
1960 50
1970 45
1980 26
1990 15
2000 12
Figure (1): Maternal mortality rate of
(country), 1960-2000
Frequency polygon
Age
(years)
Sex Mid-point of interval
Males Females
20 - 3 (12%) 2 (10%) (20+30) / 2 = 25
30 - 9 (36%) 6 (30%) (30+40) / 2 = 35
40- 7 (8%) 5 (25%) (40+50) / 2 = 45
50 - 4 (16%) 3 (15%) (50+60) / 2 = 55
60 - 70 2 (8%) 4 (20%) (60+70) / 2 = 65
Total 25(100%) 20(100%)
Frequency polygon
Age
Sex
M-P
M F
20- (12%) (10%) 25
30- (36%) (30%) 35
40- (8%) (25%) 45
50- (16%) (15%) 55
60-70 (8%) (20%) 65
0
5
10
15
20
25
30
35
40
25 35 45 55 65
Age
%
Males Females
Figure (2): Distribution of 45 patients at (place) , in
(time) by age and sex
0
1
2
3
4
5
6
7
8
9
20- 30- 40- 50- 60-69
Age in years
Frequency
Female
Male
Frequency curve
Histogram
Distribution of a group of cholera patients by age
Age (years) Frequency %
25-
30-
40-
45-
60-65
3
5
7
4
2
14.3
23.8
33.3
19.0
9.5
Total 21 100
0
5
10
15
20
25
30
35
0
2
5
3
0
4
0
4
5
6
0
6
5
Age (years)
%
Figure (2): Distribution of 100 cholera patients at (place) , in (time)
by age
Bar chart
0
5
10
15
20
25
30
35
40
45
%
Single Married Divorced Widowed
Marital status
Bar chart
0
10
20
30
40
50
%
Single Married Divorced Widowed
Marital status
Male
Female
Pie chart
Deletion
3%
Inversion
18%
Translocation
79%
Doughnut chart
Hospital A
Hospital B
DM
IHD
Renal
3-Mathematical presentation
Summery statistics
Measures of location
1- Measures of central tendency
2- Measures of non central locations
(Quartiles, Percentiles )
Measures of dispersion
1- Measures of central tendency (averages)
Midrange
Smallest observation + Largest observation
2
Mode
the value which occurs with the greatest
frequency i.e. the most common value
Summery statistics
1- Measures of central tendency (cont.)
 Median
the observation which lies in the middle of
the ordered observation.
 Arithmetic mean (mean)
Sum of all observations
Number of observations
Summery statistics
Measures of dispersion
 Range
 Variance
 Standard deviation
 Semi-interquartile range
 Coefficient of variation
 “Standard error”
Standard deviation SD
7 7
7 7 7
7
7 8
7 7 7
6 3 2
7 8 13
9
Mean = 7
SD=0
Mean = 7
SD=0.63
Mean = 7
SD=4.04
Standard error of mean SE
A measure of variability among means of samples
selected from certain population
SE (Mean) =
S
n
33861.ppt

More Related Content

Similar to 33861.ppt

Data presentation
Data presentationData presentation
Data presentation
Md. Asif Hassan
 
Gaise pre k-12_full
Gaise pre k-12_fullGaise pre k-12_full
Gaise pre k-12_full
Sarah Sue Calbio
 
04.09.21 | Making Sense of the COVID-19 Data in Persons with HIV
04.09.21 | Making Sense of the COVID-19 Data in Persons with HIV04.09.21 | Making Sense of the COVID-19 Data in Persons with HIV
04.09.21 | Making Sense of the COVID-19 Data in Persons with HIV
UC San Diego AntiViral Research Center
 
03.data presentation(2015) 2
03.data presentation(2015) 203.data presentation(2015) 2
03.data presentation(2015) 2
Mmedsc Hahm
 
Ch 3 DATA.doc
Ch 3 DATA.docCh 3 DATA.doc
Ch 3 DATA.doc
AbedurRahman5
 
Lab 1 intro
Lab 1 introLab 1 intro
Lab 1 intro
Erik D. Davenport
 
Summary Statistics_mod 1 (1).pptx
Summary Statistics_mod 1 (1).pptxSummary Statistics_mod 1 (1).pptx
Summary Statistics_mod 1 (1).pptx
PubgLegds
 
Health care waste educational intervention
Health care waste educational interventionHealth care waste educational intervention
Health care waste educational intervention
Dr.Sharad H. Gajuryal
 
Cancer burden for BOHS Nov '11
Cancer burden for BOHS Nov '11Cancer burden for BOHS Nov '11
Cancer burden for BOHS Nov '11
Retired
 
Quality of life of people live with hiv aids
Quality of life of people live with hiv aidsQuality of life of people live with hiv aids
Quality of life of people live with hiv aids
BP KOIRALA INSTITUTE OF HELATH SCIENCS,, NEPAL
 
Quality of life of people live with hiv aids
Quality of life of people live with hiv aidsQuality of life of people live with hiv aids
Quality of life of people live with hiv aids
BP KOIRALA INSTITUTE OF HELATH SCIENCS,, NEPAL
 
Descriptive Statistics
Descriptive StatisticsDescriptive Statistics
Descriptive Statistics
Kalahandi University
 
2-L2 Presentation of data.pptx
2-L2 Presentation of data.pptx2-L2 Presentation of data.pptx
2-L2 Presentation of data.pptx
ssuser03ba7c
 
Student’s presentation
Student’s presentationStudent’s presentation
Student’s presentation
Pwalmiki
 
presentation
presentationpresentation
presentation
Pwalmiki
 
Logistic regression1
Logistic regression1Logistic regression1
Logistic regression1
LoiLe36
 
Basics of statistics by Arup Nama Das
Basics of statistics by Arup Nama DasBasics of statistics by Arup Nama Das
Basics of statistics by Arup Nama Das
Arup8
 
Haplo-cord transplantation offers similar results compared to MUD transplanta...
Haplo-cord transplantation offers similar results compared to MUD transplanta...Haplo-cord transplantation offers similar results compared to MUD transplanta...
Haplo-cord transplantation offers similar results compared to MUD transplanta...cordbloodsymposium
 
Prevalence And Factors Associated With Smoking Among Students And Staff In Upm
Prevalence And Factors Associated With Smoking Among Students And Staff In UpmPrevalence And Factors Associated With Smoking Among Students And Staff In Upm
Prevalence And Factors Associated With Smoking Among Students And Staff In UpmPRN USM
 

Similar to 33861.ppt (20)

Data presentation
Data presentationData presentation
Data presentation
 
Gaise pre k-12_full
Gaise pre k-12_fullGaise pre k-12_full
Gaise pre k-12_full
 
04.09.21 | Making Sense of the COVID-19 Data in Persons with HIV
04.09.21 | Making Sense of the COVID-19 Data in Persons with HIV04.09.21 | Making Sense of the COVID-19 Data in Persons with HIV
04.09.21 | Making Sense of the COVID-19 Data in Persons with HIV
 
03.data presentation(2015) 2
03.data presentation(2015) 203.data presentation(2015) 2
03.data presentation(2015) 2
 
Ch 3 DATA.doc
Ch 3 DATA.docCh 3 DATA.doc
Ch 3 DATA.doc
 
Lab 1 intro
Lab 1 introLab 1 intro
Lab 1 intro
 
Summary Statistics_mod 1 (1).pptx
Summary Statistics_mod 1 (1).pptxSummary Statistics_mod 1 (1).pptx
Summary Statistics_mod 1 (1).pptx
 
Health care waste educational intervention
Health care waste educational interventionHealth care waste educational intervention
Health care waste educational intervention
 
Cancer burden for BOHS Nov '11
Cancer burden for BOHS Nov '11Cancer burden for BOHS Nov '11
Cancer burden for BOHS Nov '11
 
Quality of life of people live with hiv aids
Quality of life of people live with hiv aidsQuality of life of people live with hiv aids
Quality of life of people live with hiv aids
 
Quality of life of people live with hiv aids
Quality of life of people live with hiv aidsQuality of life of people live with hiv aids
Quality of life of people live with hiv aids
 
Descriptive Statistics
Descriptive StatisticsDescriptive Statistics
Descriptive Statistics
 
2-L2 Presentation of data.pptx
2-L2 Presentation of data.pptx2-L2 Presentation of data.pptx
2-L2 Presentation of data.pptx
 
Wolin opac2013
Wolin opac2013Wolin opac2013
Wolin opac2013
 
Student’s presentation
Student’s presentationStudent’s presentation
Student’s presentation
 
presentation
presentationpresentation
presentation
 
Logistic regression1
Logistic regression1Logistic regression1
Logistic regression1
 
Basics of statistics by Arup Nama Das
Basics of statistics by Arup Nama DasBasics of statistics by Arup Nama Das
Basics of statistics by Arup Nama Das
 
Haplo-cord transplantation offers similar results compared to MUD transplanta...
Haplo-cord transplantation offers similar results compared to MUD transplanta...Haplo-cord transplantation offers similar results compared to MUD transplanta...
Haplo-cord transplantation offers similar results compared to MUD transplanta...
 
Prevalence And Factors Associated With Smoking Among Students And Staff In Upm
Prevalence And Factors Associated With Smoking Among Students And Staff In UpmPrevalence And Factors Associated With Smoking Among Students And Staff In Upm
Prevalence And Factors Associated With Smoking Among Students And Staff In Upm
 

Recently uploaded

CACJapan - GROUP Presentation 1- Wk 4.pdf
CACJapan - GROUP Presentation 1- Wk 4.pdfCACJapan - GROUP Presentation 1- Wk 4.pdf
CACJapan - GROUP Presentation 1- Wk 4.pdf
camakaiclarkmusic
 
Model Attribute Check Company Auto Property
Model Attribute  Check Company Auto PropertyModel Attribute  Check Company Auto Property
Model Attribute Check Company Auto Property
Celine George
 
Chapter -12, Antibiotics (One Page Notes).pdf
Chapter -12, Antibiotics (One Page Notes).pdfChapter -12, Antibiotics (One Page Notes).pdf
Chapter -12, Antibiotics (One Page Notes).pdf
Kartik Tiwari
 
Chapter 3 - Islamic Banking Products and Services.pptx
Chapter 3 - Islamic Banking Products and Services.pptxChapter 3 - Islamic Banking Products and Services.pptx
Chapter 3 - Islamic Banking Products and Services.pptx
Mohd Adib Abd Muin, Senior Lecturer at Universiti Utara Malaysia
 
BÀI TẬP BỔ TRỢ TIẾNG ANH GLOBAL SUCCESS LỚP 3 - CẢ NĂM (CÓ FILE NGHE VÀ ĐÁP Á...
BÀI TẬP BỔ TRỢ TIẾNG ANH GLOBAL SUCCESS LỚP 3 - CẢ NĂM (CÓ FILE NGHE VÀ ĐÁP Á...BÀI TẬP BỔ TRỢ TIẾNG ANH GLOBAL SUCCESS LỚP 3 - CẢ NĂM (CÓ FILE NGHE VÀ ĐÁP Á...
BÀI TẬP BỔ TRỢ TIẾNG ANH GLOBAL SUCCESS LỚP 3 - CẢ NĂM (CÓ FILE NGHE VÀ ĐÁP Á...
Nguyen Thanh Tu Collection
 
Biological Screening of Herbal Drugs in detailed.
Biological Screening of Herbal Drugs in detailed.Biological Screening of Herbal Drugs in detailed.
Biological Screening of Herbal Drugs in detailed.
Ashokrao Mane college of Pharmacy Peth-Vadgaon
 
A Survey of Techniques for Maximizing LLM Performance.pptx
A Survey of Techniques for Maximizing LLM Performance.pptxA Survey of Techniques for Maximizing LLM Performance.pptx
A Survey of Techniques for Maximizing LLM Performance.pptx
thanhdowork
 
Francesca Gottschalk - How can education support child empowerment.pptx
Francesca Gottschalk - How can education support child empowerment.pptxFrancesca Gottschalk - How can education support child empowerment.pptx
Francesca Gottschalk - How can education support child empowerment.pptx
EduSkills OECD
 
The basics of sentences session 5pptx.pptx
The basics of sentences session 5pptx.pptxThe basics of sentences session 5pptx.pptx
The basics of sentences session 5pptx.pptx
heathfieldcps1
 
How to Make a Field invisible in Odoo 17
How to Make a Field invisible in Odoo 17How to Make a Field invisible in Odoo 17
How to Make a Field invisible in Odoo 17
Celine George
 
Normal Labour/ Stages of Labour/ Mechanism of Labour
Normal Labour/ Stages of Labour/ Mechanism of LabourNormal Labour/ Stages of Labour/ Mechanism of Labour
Normal Labour/ Stages of Labour/ Mechanism of Labour
Wasim Ak
 
Digital Artifact 2 - Investigating Pavilion Designs
Digital Artifact 2 - Investigating Pavilion DesignsDigital Artifact 2 - Investigating Pavilion Designs
Digital Artifact 2 - Investigating Pavilion Designs
chanes7
 
STRAND 3 HYGIENIC PRACTICES.pptx GRADE 7 CBC
STRAND 3 HYGIENIC PRACTICES.pptx GRADE 7 CBCSTRAND 3 HYGIENIC PRACTICES.pptx GRADE 7 CBC
STRAND 3 HYGIENIC PRACTICES.pptx GRADE 7 CBC
kimdan468
 
The approach at University of Liverpool.pptx
The approach at University of Liverpool.pptxThe approach at University of Liverpool.pptx
The approach at University of Liverpool.pptx
Jisc
 
Introduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp NetworkIntroduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp Network
TechSoup
 
Acetabularia Information For Class 9 .docx
Acetabularia Information For Class 9  .docxAcetabularia Information For Class 9  .docx
Acetabularia Information For Class 9 .docx
vaibhavrinwa19
 
special B.ed 2nd year old paper_20240531.pdf
special B.ed 2nd year old paper_20240531.pdfspecial B.ed 2nd year old paper_20240531.pdf
special B.ed 2nd year old paper_20240531.pdf
Special education needs
 
Unit 8 - Information and Communication Technology (Paper I).pdf
Unit 8 - Information and Communication Technology (Paper I).pdfUnit 8 - Information and Communication Technology (Paper I).pdf
Unit 8 - Information and Communication Technology (Paper I).pdf
Thiyagu K
 
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
MysoreMuleSoftMeetup
 
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
Levi Shapiro
 

Recently uploaded (20)

CACJapan - GROUP Presentation 1- Wk 4.pdf
CACJapan - GROUP Presentation 1- Wk 4.pdfCACJapan - GROUP Presentation 1- Wk 4.pdf
CACJapan - GROUP Presentation 1- Wk 4.pdf
 
Model Attribute Check Company Auto Property
Model Attribute  Check Company Auto PropertyModel Attribute  Check Company Auto Property
Model Attribute Check Company Auto Property
 
Chapter -12, Antibiotics (One Page Notes).pdf
Chapter -12, Antibiotics (One Page Notes).pdfChapter -12, Antibiotics (One Page Notes).pdf
Chapter -12, Antibiotics (One Page Notes).pdf
 
Chapter 3 - Islamic Banking Products and Services.pptx
Chapter 3 - Islamic Banking Products and Services.pptxChapter 3 - Islamic Banking Products and Services.pptx
Chapter 3 - Islamic Banking Products and Services.pptx
 
BÀI TẬP BỔ TRỢ TIẾNG ANH GLOBAL SUCCESS LỚP 3 - CẢ NĂM (CÓ FILE NGHE VÀ ĐÁP Á...
BÀI TẬP BỔ TRỢ TIẾNG ANH GLOBAL SUCCESS LỚP 3 - CẢ NĂM (CÓ FILE NGHE VÀ ĐÁP Á...BÀI TẬP BỔ TRỢ TIẾNG ANH GLOBAL SUCCESS LỚP 3 - CẢ NĂM (CÓ FILE NGHE VÀ ĐÁP Á...
BÀI TẬP BỔ TRỢ TIẾNG ANH GLOBAL SUCCESS LỚP 3 - CẢ NĂM (CÓ FILE NGHE VÀ ĐÁP Á...
 
Biological Screening of Herbal Drugs in detailed.
Biological Screening of Herbal Drugs in detailed.Biological Screening of Herbal Drugs in detailed.
Biological Screening of Herbal Drugs in detailed.
 
A Survey of Techniques for Maximizing LLM Performance.pptx
A Survey of Techniques for Maximizing LLM Performance.pptxA Survey of Techniques for Maximizing LLM Performance.pptx
A Survey of Techniques for Maximizing LLM Performance.pptx
 
Francesca Gottschalk - How can education support child empowerment.pptx
Francesca Gottschalk - How can education support child empowerment.pptxFrancesca Gottschalk - How can education support child empowerment.pptx
Francesca Gottschalk - How can education support child empowerment.pptx
 
The basics of sentences session 5pptx.pptx
The basics of sentences session 5pptx.pptxThe basics of sentences session 5pptx.pptx
The basics of sentences session 5pptx.pptx
 
How to Make a Field invisible in Odoo 17
How to Make a Field invisible in Odoo 17How to Make a Field invisible in Odoo 17
How to Make a Field invisible in Odoo 17
 
Normal Labour/ Stages of Labour/ Mechanism of Labour
Normal Labour/ Stages of Labour/ Mechanism of LabourNormal Labour/ Stages of Labour/ Mechanism of Labour
Normal Labour/ Stages of Labour/ Mechanism of Labour
 
Digital Artifact 2 - Investigating Pavilion Designs
Digital Artifact 2 - Investigating Pavilion DesignsDigital Artifact 2 - Investigating Pavilion Designs
Digital Artifact 2 - Investigating Pavilion Designs
 
STRAND 3 HYGIENIC PRACTICES.pptx GRADE 7 CBC
STRAND 3 HYGIENIC PRACTICES.pptx GRADE 7 CBCSTRAND 3 HYGIENIC PRACTICES.pptx GRADE 7 CBC
STRAND 3 HYGIENIC PRACTICES.pptx GRADE 7 CBC
 
The approach at University of Liverpool.pptx
The approach at University of Liverpool.pptxThe approach at University of Liverpool.pptx
The approach at University of Liverpool.pptx
 
Introduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp NetworkIntroduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp Network
 
Acetabularia Information For Class 9 .docx
Acetabularia Information For Class 9  .docxAcetabularia Information For Class 9  .docx
Acetabularia Information For Class 9 .docx
 
special B.ed 2nd year old paper_20240531.pdf
special B.ed 2nd year old paper_20240531.pdfspecial B.ed 2nd year old paper_20240531.pdf
special B.ed 2nd year old paper_20240531.pdf
 
Unit 8 - Information and Communication Technology (Paper I).pdf
Unit 8 - Information and Communication Technology (Paper I).pdfUnit 8 - Information and Communication Technology (Paper I).pdf
Unit 8 - Information and Communication Technology (Paper I).pdf
 
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
 
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
 

33861.ppt

  • 2. Introduction to Biostatistics Dr. Moataza Mahmoud Abdel Wahab Lecturer of Biostatistics High Institute of Public Health University of Alexandria
  • 3. Biostatistics (a portmanteau word made from biology and statistics) The application of statistics to a wide range of topics in biology.
  • 4. Biostatistics It is the science which deals with development and application of the most appropriate methods for the: Collection of data. Presentation of the collected data. Analysis and interpretation of the results. Making decisions on the basis of such analysis
  • 5. Other definitions for “Statistics”  Frequently used in referral to recorded data  Denotes characteristics calculated for a set of data : sample mean
  • 6. Role of statisticians  To guide the design of an experiment or survey prior to data collection  To analyze data using proper statistical procedures and techniques  To present and interpret the results to researchers and other decision makers
  • 7. Sources of data Records Surveys Experiments Comprehensive Sample
  • 9. Quantitative continuous Types of variables Quantitative variables Qualitative variables Quantitative descrete Qualitative nominal Qualitative ordinal
  • 10.  Numerical presentation  Graphical presentation  Mathematical presentation Methods of presentation of data
  • 11. 1- Numerical presentation Tabular presentation (simple – complex) Simple frequency distribution Table (S.F.D.T.) Title Name of variable (Units of variable) Frequency % - - Categories - Total
  • 12. Table (I): Distribution of 50 patients at the surgical department of Alexandria hospital in May 2008 according to their ABO blood groups Blood group Frequency % A B AB O 12 18 5 15 24 36 10 30 Total 50 100
  • 13. Table (II): Distribution of 50 patients at the surgical department of Alexandria hospital in May 2008 according to their age Age (years) Frequency % 20-<30 30- 40- 50+ 12 18 5 15 24 36 10 30 Total 50 100
  • 14. Complex frequency distribution Table Table (III): Distribution of 20 lung cancer patients at the chest department of Alexandria hospital and 40 controls in May 2008 according to smoking Smoking Lung cancer Total Cases Control No. % No. % No. % Smoker 15 75% 8 20% 23 38.33 Non smoker 5 25% 32 80% 37 61.67 Total 20 100 40 100 60 100
  • 15. Complex frequency distribution Table Table (IV): Distribution of 60 patients at the chest department of Alexandria hospital in May 2008 according to smoking & lung cancer Smoking Lung cancer Total positive negative No. % No. % No. % Smoker 15 65.2 8 34.8 23 100 Non smoker 5 13.5 32 86.5 37 100 Total 20 33.3 40 66.7 60 100
  • 16. 2- Graphical presentation  Graphs drawn using Cartesian coordinates • Line graph • Frequency polygon • Frequency curve • Histogram • Bar graph • Scatter plot  Pie chart  Statistical maps rules
  • 17. Line Graph 0 10 20 30 40 50 60 1960 1970 1980 1990 2000 Year MMR/1000 Year MMR 1960 50 1970 45 1980 26 1990 15 2000 12 Figure (1): Maternal mortality rate of (country), 1960-2000
  • 18. Frequency polygon Age (years) Sex Mid-point of interval Males Females 20 - 3 (12%) 2 (10%) (20+30) / 2 = 25 30 - 9 (36%) 6 (30%) (30+40) / 2 = 35 40- 7 (8%) 5 (25%) (40+50) / 2 = 45 50 - 4 (16%) 3 (15%) (50+60) / 2 = 55 60 - 70 2 (8%) 4 (20%) (60+70) / 2 = 65 Total 25(100%) 20(100%)
  • 19. Frequency polygon Age Sex M-P M F 20- (12%) (10%) 25 30- (36%) (30%) 35 40- (8%) (25%) 45 50- (16%) (15%) 55 60-70 (8%) (20%) 65 0 5 10 15 20 25 30 35 40 25 35 45 55 65 Age % Males Females Figure (2): Distribution of 45 patients at (place) , in (time) by age and sex
  • 20. 0 1 2 3 4 5 6 7 8 9 20- 30- 40- 50- 60-69 Age in years Frequency Female Male Frequency curve
  • 21. Histogram Distribution of a group of cholera patients by age Age (years) Frequency % 25- 30- 40- 45- 60-65 3 5 7 4 2 14.3 23.8 33.3 19.0 9.5 Total 21 100 0 5 10 15 20 25 30 35 0 2 5 3 0 4 0 4 5 6 0 6 5 Age (years) % Figure (2): Distribution of 100 cholera patients at (place) , in (time) by age
  • 23. Bar chart 0 10 20 30 40 50 % Single Married Divorced Widowed Marital status Male Female
  • 26. 3-Mathematical presentation Summery statistics Measures of location 1- Measures of central tendency 2- Measures of non central locations (Quartiles, Percentiles ) Measures of dispersion
  • 27. 1- Measures of central tendency (averages) Midrange Smallest observation + Largest observation 2 Mode the value which occurs with the greatest frequency i.e. the most common value Summery statistics
  • 28. 1- Measures of central tendency (cont.)  Median the observation which lies in the middle of the ordered observation.  Arithmetic mean (mean) Sum of all observations Number of observations Summery statistics
  • 29. Measures of dispersion  Range  Variance  Standard deviation  Semi-interquartile range  Coefficient of variation  “Standard error”
  • 30. Standard deviation SD 7 7 7 7 7 7 7 8 7 7 7 6 3 2 7 8 13 9 Mean = 7 SD=0 Mean = 7 SD=0.63 Mean = 7 SD=4.04
  • 31. Standard error of mean SE A measure of variability among means of samples selected from certain population SE (Mean) = S n