2. بسم الله الرحمن الرحيم

3. Dr. Laila Mohamed Nofal Professor of Biostatistics High Institute of Public Health University of Alexandria

4. 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.

5.  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

6.  One quantitative variable & Time.  Time may be years, months, weeks, days, hours…)  No frequency distribution.  May be one or more quantitative variables by time.

7. The Line Graph Example: YearCrude Birth Rate Per 1000 Population 199750 199851 199953 200055 200152

8. The Line Graph Figure (1) Crude birth rate of Country X 1997-2001

10. The Line Graph

11. For quantitative continuous variables S.F.D.T only

12. Example: Age in YearsFrequency 0 -4 5 -10 10 –18 15 –8 20 - 246 Total46

13. Example: Age in Years Figure (2): Distribution of patients by age in Hospital X, 2011

14. Quantitative continuous variable SFDT or Complex FDT

15. SFDT Points are joined by straight line

16. Complex FDT Points are joined by straight line

17. Distribution of a group of patients by age Age group Freq.RelativeFreq.(%) Mid-Point (abscissa) 20-612.2(20+30)/2=25 30-1836.7(30+40)/2=35 40-1122.5(40+50)/2=45 50-1122.5(50+60)/2=55 60-6936.1(60+70)/2=65 Total49100.0%

18. Distribution of a group of patients by age

19. 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

20. Figure (3): Distribution of patients by age and sex in Hospital X, 2012

21. 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

22. Distribution of malaria cases by age

23. Qualitative or quantitative discrete variables Simple or complex frequency table

24. Simple frequency table

25. Complex frequency table

26. Example

27. Bars should be of equal widths and inter bar spacing and differ only in height

28. Example

30. 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

31. The Pie Chart Angle for single = 20 x360 = 100 ⁰ 72 Angle for married = 30 x360 = 150 ⁰ 72 Angle for widowed= 10 x360 = 50 ⁰ 72 Angle for divorced= 20 x360 = 60 ⁰ 72 Total = 100+150+50+60= 360 ⁰ Marital StatusFrequency Single20 Married30 Divorced10 Widowed12 Total72

32. The Pie Chart Figure (4): Distribution of patients by marital status in Hospital X, in the year 2012

33. Pie Chart Distribution of patients according to their blood group and sex Blood Group Sex MaleFemale Freq. Rel. Freq. (%)Freq.Rel.Freq.(%) A2027.81525.9 B3041.71831.0 AB1013.91322.4 O1216.61220.7 Total72100.058100.0

34. Pie Chart Distribution of patients according to their blood group and sex Male Female

35. GraphsGraphs QuantitativeDataQuantitativeData SFDT Freq. Polygon Freq. Polygon Freq. Polygon Freq. Polygon Histogram QualitativeDataQualitativeData ComplexSFDT Bar Chart Bar Chart Pie Chart Pie Chart Bar Chart Bar ChartComplex ContinuousDiscrete Bar Chart Bar ChartDiscrete Continuous Bar Chart Bar Chart