Unit-10 Data Management & Presentation Provid By Immam.pptx

Students will be able to know about the data management and presentation that help to brighten their futures that are easy to understand these things from this slide.................................

1. Data Management & Presentation By: Ibne Amin Institute of Nursung sciences Khyber Medical University,Peshawar

2. Objectives Define the term data Discuss the types of data and various methods of data collection. Discuss the different means and interpretation of data presentation through: Graphs, Tables, Charts.

3. Data DATA are informations which may lead to an answer or a solution to a particular question or a problem OR Collection of information in numerical form. (Data are numerical facts) OR The values of observations recorded for variables OR Informations,coming  from observations, counts,  measurements,or  response (Singular = datum) VARIABLE a variable is defined as  anything that has a quantity  or quality that varies.

4. Types of Data 1.Quantitative data Numerical data that you can add, subtract, multiply, and divide Numerical values, often with units of measurement Examples: • Age (possible units: years) • Blood pressure (mm of Hg) • BMI (kg/m2) • Pulse (beats/minute) • Annual income (possible units: thousands of PKR) • Number of children (count therefore no other units) • Optimism on a 0 to 100 scale • Exercise in hours per week • Coffee drinking in ounces per day

5. Types of Data 2. Qualitative Data Also called categorical data When the data are arranged in categories on the basis of their quality or attribute and there is gap between two values, it is called qualitative data, e.g name, religion, marital status, socioeconomic status, awareness. Qualitative data cannot be expressed in numerical forms.

6. Source of Data Collection Routinely kept records External sources Natural observation : Survey Case study : Experiment :

7. Source of Data Collection Routinely kept records It is difficult to imagine any type of organization that does not keep records of day-to-day transactions of its activities. Hospital medical records, for example, contain immense amounts of information on patients, while hospital accounting records contain a wealth of data on the facility’s business activities. When the need for data arises, we should look for them first among routinely kept records.

8. Source of Data Collection External sources The data needed to answer a question may already exist in the form of published reports, commercially available data banks, or the research literature. In other words, we may find that someone else has already asked the same question, and the answer obtained may be applicable to our present situation.

9. Source of Data Collection Natural observation : Go out into the field and observe phenomena (People, animal), and if possible without interfering with the phenomena itself

10. Source of Data Collection Survey It is also kind of observational study. You are just collecting information without having any control

11. Source of Data Collection Case study : One unusual individual is intensively studied

12. Source of Data Collection Experiment : Where one variable is deliberately manipulated. It is a kind of research plan that have another group called controls.

13. Data Presentation Summarize data in an informative and accurate way Help reader grasp the key feature of the data The goal is have a graphic that is simple, easy  to understand, and  most effective in presenting the data to the general public. 

14. 14 Presentation of Data Statistical data are generally presented by: Tables - Frequency table - Cross-tabulation Graphs - For Qualitative data - For Quantitative data

15. 15 Presentation of qualitative Data by Table A Psychologist asked a list of questions to measure the level of Anxiety and Depression in the patient. In one of the question she asked: “Have you had lack of interest in your daily activities during past two weeks?” Code: 0=Never; 1=few times; 2=often; 3=Always The responses of 20 randomly selected patients for the above question were: Few times; Always; Never; Often; Often; Often; Always; Few times; Often; Always; Often; Never; Always; Often; Always; Often; Often; Few times; Often; Always;

16. 16 Presentation of Qualitative Data by Table ________________________________________________________________ Response Frequency Relative Frequency _ Tally Number of Marks Patients Proportion Never II 2 2/20=0.10 Few Times III 3 3/20=0.15 Often IIIIIIII 9 9/20=0.45 Always IIIII 6 6/20=0.30 _________________________________________________________________ Total 20 1.00 Note: Relative frequency can also be presented in times of percentage by multiplying 100.

17. 17 Presentation of Quantitative Data by Table Problem Description: The class of 2004 at the Isra University conducted a baseline sample survey at Rehri Goth for the E mergency obstetric care project. As the baseline information, the students also asked about the number of living children per women (15-49 years). The following data has been collected based on a random sample of n=30 woman. 2,2,5,3,0,1,3,2,3,4,1,3,4,5,7, 3,2,4,1,0,5,8,6,5,4, 2,4,4,7,6

18. 18 Presentation of Quantitative Data by T able Number of Cumulative Living children Tally Frequency Frequency II 2 2 1 III 3 5 2 IIII 5 10 3 IIII 5 15 4 IIIII 6 21 5 IIII 4 25 6 II 2 27 7 II 2 29 8 I 1 30 _______________________________________________ Total 30

19. 19 What happened when you have a lot of different observation? Problem description: A sample survey was conducted in a squatter (thicker, unlawful residents, shorter) settlement of Karachi, the households were asked about the average monthly amount (in Rs.) spent on health by them? The following data was collected based on random sample of n=25 households. 90,75,140,80,60,55,105,70,298,180,105, 130,145,150,270,235,125,245,100,205,50, 85,160,275,194.

20. 20 Steps to summarize the into Frequency Distribution Table The following steps should be taken: Step 1: compute the interval spanned by the data. We can obtain this interval by arranging the data into an array, a listing all observations from smallest to Largest. 50,55,60,70,80,85,90,100,105,105,125,130,140 145,150,160,180,194,205,235,245,270,275,298

21. 21 Step 2: Divide the range into an arbitrary number but usually equal and non-overlapping segments (each data value belonging to one and only one segments) called class intervals. The number of intervals depends on the number of observations but in general should range from 5 to 15. Suppose we want to group the data into five non-overlapping classes Approximate Class Width = Largest data value – Smallest data value Number of Classes 298 -50 = 248 = 49.6 5 5 Rounding up, we choose to create five classes of width of 50 each

22. Expenditure on Health (Rs.) Tally Frequency Relative Cumulative Frequency 50-99 IIIIIII 08 8/25= 0.32 100-149 IIIIII 07 0.60 150-199 IIII 04 0.76 200-249 III 03 0.88 250-299 III 03 1.00 Total 25 Note: Relative Frequency can also be presented in terms of percentage by multiplying 100

23. 23 Class Lower Limit Upper Limit Midpoint Frequency Relative Frequency Cumulative Frequency Cum. Rel. Frequency 62 66 64 1 66 70 68 1 0.01 1 0.01 2 70 74 72 1 0.01 3 74 78 76 1 0.01 4 78 82 80 2 0.02 3 0.03 5 82 86 84 8 0.08 11 0.11 6 86 90 88 5 0.05 16 0.16 7 90 94 92 14 0.14 30 0.3 8 94 98 96 18 0.18 48 0.48 9 98 102 100 11 0.11 59 0.59 10 102 106 104 18 0.18 77 0.77 11 106 110 108 6 0.06 83 0.83 12 110 114 112 8 0.08 91 0.91 13 114 118 116 5 0.05 96 0.96 14 118 122 120 3 0.03 99 0.99 15 122 126 124 1 0.01 100 1 16 126 130 128 100 1 17 130 134 132 100 1 18 134 138 136 100 1 19 138 142 140 100 1 20 142 146 144 100 1 21 146 150   100 1

24. 24 Cross tabulation (or crosstabs for short): It is a statistical process that summarizes categorical data to create a contingency table.. They provide a basic picture of the interrelation between two variables and can help find interactions between them. Presentation of Data by Cross Tabulation

25. 25 Sample # Gender Handedness 1 Female Right-handed 2 Male Left-handed 3 Female Right-handed 4 Male Right-handed 5 Male Left-handed 6 Male Right-handed 7 Female Right-handed 8 Female Left-handed 9 Male Right-handed 10 Female Right-handed :

26. 26

27. Cross-Tabulation Contingency table 27 Left handed Right handed total Males 2 3 5 Females 1 4 5 total 3 7 10

28. 28 Graphs Graphs are Geometrical designs: Convey information at a glance Mathematically less sophisticated (no formula used, no calculations)

29. 29 Graphical Presentation of Quantitative Data Histogram Frequency Polygon Stem and Leaf

30. Conti Histogram Used for Quantitative, Continuous, Variables. It is used to present variables which have no gaps e.g age, weight, height, blood pressure, blood sugar etc. It consist of a series of blocks. The class intervals are given along horizontal axis and the frequency along the vertical axis.

31. 31 Presentation Histogram Similar to bar chart  bars closely situated # of bars? Too few  data clumps Too many  overly detailed

32. 32 AGE 80.0 75.0 70.0 65.0 60.0 55.0 50.0 45.0 40.0 35.0 HISTOGRAM FREQUENCY INDIVIDUALS 14 12 10 8 6 4 2 Std. Dev = 10.06 Mean = 57.7 N = 50.00

33. Conti… Frequency polygon Frequency polygon is an area diagram of frequency distribution over a histogram. It is a linear representation of a frequency table and histogram, obtained by joining the mid points of the hitogram blocks. Frequency is plotted at the central point of a group percentage

34. 34

35. 35 STEM & LEAF GRAPH

36. STEM & LEAF GRAPH

37. 37 Graphical Presentation of Qualitative Data Simple Bar chart Multiple Bar chart Component Bar Chart Sliding Bar Chart (e.g. Population Pyramid) Pie Chart

38. 38 BAR CHART Sex Female Male Frequency 80 70 60 50

39. 39 MULTIPLE BAR CHART (VERTICAL) GENDER Female Male ASCITES 60 50 40 30 20 10 Ascites Yes No

40. 40 SLIDING BAR CHART

41. 41 PIE CHART Figure 2.3 Pie chart showing the number of students of each category  

42. References Biostatistics by Prem P. Panta Fundamentals of Research Methodology and Statistics by Yogesh k. Singh Research Design by J. W. Creswell Internet