Methods of data presention

2,824 views

Published on

0 Comments
4 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
2,824
On SlideShare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
Downloads
127
Comments
0
Likes
4
Embeds 0
No embeds

No notes for slide

Methods of data presention

  1. 1. METHODS OF DATA PRESENTATION DR. VAIBHAV GUPTA MPH 1st year Student Dept. of community medicine JSSMC 27/03/13 Moderated by: Mrs. Vidyalaxmi 1
  2. 2. Types of Data Types of Data Quantitative Data Qualitative Data 2
  3. 3. Types of Data Quantitative data are measurements that are recorded on a naturally occurring numerical scale. Exp. Height in cm. ,weight in kg. ,blood pressure (mm/Hg) Qualitative data are measurements that cannot be measured on a natural numerical scale; they can only be classified into one of a group of categories. Exp . Sex, tall or short, blood group 3
  4. 4. Presentation of data • Frequency distribution table • Graphic&Diagrametic presentation 4
  5. 5. Class Frequency, f 1 – 4 4 5 – 8 5 9 – 12 3 13 – 16 4 17 – 20 2 Frequency Distributions A frequency distribution is a table that shows classes or intervals of data with a count of the number in each class. The frequency f means the number of times a certain value of variable is repeated. Frequencies 5
  6. 6. Class Frequency, f 1 – 4 4 5 – 8 5 9 – 12 3 13 – 16 4 17 – 20 2 Class width The class width is the distance between lower (or upper) limits of consecutive classes. The class width is 3. 4 – 1 = 3 8 – 5 = 3 12 – 9 = 3 13-16=3 6
  7. 7. Guidelines 1. Condense the data by classifying them in to groups or classes called as class intervals.. 2. It is best to select class intervals of equal size. 3. Find the class width 4. Find the class limits. You can use the minimum entry as the lower limit of the first class. To find the remaining lower limits, add the class width to the lower limit of the preceding class. Then find the upper class limits. 5. Make a tally mark for each data entry in the row of the appropriate class. 7
  8. 8. CONT……….. 6. Count the tally marks to find the total frequency f for each class. 7. Class limits are specially started either inclusive or exclusive manner. 8. Inclusive manner- 45-49;50-54;55-59…. 9. Excusive manner-45-50;50-55;55-60…. 10.Interval may be represented by midpoints of class interval. 8
  9. 9. Constructing a Frequency Distribution 18 20 21 27 29 20 19 30 32 19 34 19 24 29 18 37 38 22 30 39 32 44 33 46 54 49 18 51 21 21 Example: The following data represents the ages of 30 students in a statistics class. Construct a frequency distribution that has five classes. Ages of Students 9
  10. 10. Constructing a Frequency Distribution Example continued: 250 – 57 342 – 49 434 – 41 826 – 33 1318 – 25 Tally Frequency, fClass 30f Number of students Ages Check that the sum equals the number in the sample. Ages of Students 10
  11. 11. Midpoint The midpoint of a class is the sum of the lower and upper limits of the class divided by two. The midpoint is sometimes called the class mark. Midpoint = (Lower class limit) + (Upper class limit) 2 Frequency, fClass Midpoint 41 – 4 Midpoint = 1 2 4 5 2 2.5 2.5 11
  12. 12. Relative Frequency Class Frequency, f Relative Frequency 1 – 4 4 The relative frequency of a class is the portion or percentage of the data that falls in that class. To find the relative frequency of a class, divide the frequency f by the sample size n. Relative frequency =Class frequency Sample size Relative frequency 8 4 1 0.222 0.222 f n 18f f n 12
  13. 13. Cumulative Frequency The cumulative frequency of a class is the sum of the frequency for that class and all the previous classes. 30 28 25 21 13 Total number of students + + + +50 – 57 2 3 4 8 13 42 – 49 34 – 41 26 – 33 18 – 25 Frequency, fClass 30f Cumulative Frequency Ages of Students 13
  14. 14. Graphical &Diagrammatic Presentation • It provides a visual method of examining quantitative and qualitative data. • It brings out clear and relative importance of different figures and helpful in finding out relation between two or more sets of data. a. Presentation of qualitative data: A. Bar diagrams B. Line diagrams C. Pie diagrams 14
  15. 15. CONT……… D. Pictograms. E. Map diagrams. b. Presentation of quantitative data A. Histogram B. Frequency polygon C. Cumulative frequency curve or ogive D. Scattered diagram 15
  16. 16. Presentation of qualitative data: (A)Bar diagram 16
  17. 17. (B)The Line diagram 17 Example: Figure (1) Crude birth rate of Gaza Strip . 1997-2001
  18. 18. (C)The Pie Chart CC 18 Marital Status Frequency % Single 20 28 Married 30 41 Divorced 10 14 Widowed 12 17 Total 72 100 Distribution of a group of subjects by marital status
  19. 19. (D)Pictogram 19 Fireflies
  20. 20. 2020
  21. 21. 21 Presentation of quantitative data 1.The Histogram Examples: Age in Years Number of patients 0 - 5 4 5 - 10 10 10 - 15 18 15 - 20 8 20 - 25 6 Total 46
  22. 22. 22 The Histogram Examples: Number of patients Age in Years Distribution of a group of subjects by age
  23. 23. 23 2.The Frequency Polygon • Examples: Age in Years Sex Mid-point of interval Males Females 20-30 (20+30)/2=25 30-40 (30+40)/2=35 40-50 (40+50)/2=45 50-60 (50+60)/2=55 60-70 (60+70)/2=65 Total
  24. 24. The Frequency Polygon • Example: Figure (2): Distribution of a group of subjects by age and sex 24
  25. 25. 25 3.Cumulative Frequency Graph A cumulative frequency graph or ogive, is a line graph that displays the cumulative frequency of each class at its upper class boundary. 17.5 Age (in years) Ages of Students 24 18 12 6 30 0 Cumulativefrequency (portionofstudents) 25.5 33.5 41.5 49.5 57.5 The graph ends at the upper boundary of the last class.
  26. 26. 26 Class Boundaries Example: Find the class boundaries for the “Ages of Students” frequency distribution. 49.5 57.5 41.5 49.5 33.5 41.5 25.5 33.5 17.5 25.5The distance from the upper limit of the first class to the lower limit of the second class is 1. Half this distance is 0.5. Class Boundaries 50 – 57 2 3 4 8 13 42 – 49 34 – 41 26 – 33 18 – 25 Frequency, fClass 30f Ages of Students
  27. 27. 27 4.The Scatter Diagram • When two quantitative variables such as blood pressure and weight have been measured on the same set of individuals, a simple and effective way of describing them is the scatter diagram. • Each individual’s X (first variable value) and y (2nd variable value) measurements are plotted as a point on the diagram. • The X value plotted on the horizontal scale. • The Y value on the vertical scale. • For example for the data below, the first individual’s weight is 67 kg, his blood pressure is 114 mmHg. • The marked point in the figure corresponds to this individual's weight and blood pressure. Weight (kg) 67 69 85 83 74 81 97 92 114 SBP (mmHg) 114 90 88 96 113 92 103 123 125
  28. 28. 28 The Scatter diagram Weight (kg) 67 69 85 83 74 81 97 92 114 SBP (mmHg) 114 90 88 96 113 92 103 123 125 Scatter diagram of weight and systolic blood pressure for a group of individuals
  29. 29. Thank you 29

×