Biostatistics

method of sampling and data presentation

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2. (part-1) BIOSTATISTICS 7/21/2016 2

3. Date-21/07/2016 Topic – Biostatistics (part-1) Duration – 40 minutes Subject – Public Health Dentistry Time Of Class –3.00-4.00pm Target audience –final year B.D.S students Method of presentation – PowerPoint presentation Audio & Visual Aids Used – LCD Projector & Laptop Objectives- By the end of the class, students should understand the method of data presentation and types of sampling, Method of evaluation- by asking questions at the end of the class 7/21/2016 3

4. Lesson plan Topic : Biostatistics part-1 Year: B.D.S VI year Date: 21/07/2016 Time: 3:00 pm -4:00 pm Setting: Aim : to teach about the method of data presentation and types of sampling. Learning objectives : The students should learn about the method of data presentation and types of sampling Sl . No. CONTENT TL Methods TL Media Time 1. Introduction Lecture Power point 10 mins 2. -Presentation of data . Lecture Power point 2 mins 3. Sampling techniques . Lecture Power point 20 mins 4. Sampling Error Lecture Power point 15 mins . 5. Non Sampling Discussion Power point 10mins 7/21/2016 4

5. Contents:- Introduction Presentation of data - Methods of presentation Data. Sampling techniques Sampling Error Non Sampling error References 7/21/2016 5

6. INTRODUCTION The word “Statistics” is derived from Latin for ‘state’ indicating historical importance of data gathering, which principally is demographic information. Statistics is the science, which deals with collection, organization, summarization, analysis, interpretation and presentation of data. Inferences derived from these findings help in making valid decisions. Statistical methods and techniques applied to biological problems or data is called Biostatistics. 7/21/2016 6

7. Presentation of Data What is Data? -facts and statistics collected together for reference or analysis. Data collected from various experiments. It should be compiled, classified and presented in a purposive manner to bring out important points. 7/21/2016 7

8. Methods of Presentation of Data. Based on the data type, representation of data also differs. There are two different types of data in statistics; they are; discrete, and continuous type of data. Discrete data are distinct and separate and also invariably whole numbers. eg . Number of deaths due to particular diseases. 7/21/2016 8

9. Continuous data are those, which takes the value between range of values, eg height, weight, age. There are two methods of presenting the data:- Tabulation Charts and diagrams 7/21/2016 9

10. Tabulation (frequency distribution table):- The distribution of the total no. of observation among the various categories is termed as a frequency distribution . 7/21/2016 10

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12. Charts and diagrams:- Presenting data in these forms is useful in simplifying the presentation and enhancing comprehension of the data. Representation of data in these form provides the following:- 7/21/2016 12

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14. Bar chart:- These are the way of presenting a set of numbers by length of a bar; the length of the bar is proportional to the magnitude to be represented. Bar charts are easy to prepare, easy to understand and enable visual comparison. There are three types of bar charts:- Simple bar chart Multiple bar chart Component bar charts FOR DISCRETE DATA 7/21/2016 14

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17. 7/21/2016 17 Component bar graph showing male and female ratio

18. 2. Pie chart:- In these diagrams the areas of segments of a circle are compared. The area of each segment depends upon the percentage, which is converted to angle and drawn. 7/21/2016 18

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20. 3 . Pictogram:- These diagrams are used for a layman those who cannot understand technical charts like bar charts. Here pictures and symbols are used to present the data. 7/21/2016 20

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22. Histogram:- Histogram is a set of vertical bars whose areas are proportional to the frequencies represented. The class intervals are given along the horizontal axis and the frequencies along the vertical axis. FOR CONTINUOUS DATA 7/21/2016 22

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24. 2. Line charts:- It shows trends or changes in data varying with a constant, at even intervals. A line chart emphasizes the flow of a constant and rate of change, rather than amount of change. When we need to show trends or changes in data at uneven or clustered intervals, an XY (scatter) chart is used . 7/21/2016 24

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26. 3. Frequency curve:- A frequency polygon is a graphical display of a frequency table. The intervals are shown on the x-axis and the number of the scores in each interval is represented by the height of a point located above the middle of the interval. The points are connected so that together with the X-axis they form a polygon. 7/21/2016 26

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28. SAMPLING TECHNIQUES The study population is too large and it may be too expensive or too time consuming to attempt either a complete or nearly complete coverage in a statistical study, so we take a sample from the population. Sample is the representative of the population and to ensure that we chose each unit of the sample technically. This process is called sampling technique. Sufficient sample size is calculated based on the proportion of and precision required . 7/21/2016 28

29. There are two methods in sampling techniques :- 7/21/2016 29

30. Simple random sampling It is applicable when:- The population is small. The population is available the population is homogenous. This is done either by using random table or lottery method. The principle used to select the sample is each and every unit will have equal chance of getting selected . 7/21/2016 30

31. Systematic sampling This technique is applicable when:- The population is large and scattered but the population list available (sampling frame), and The population is not homogeneous. The principle used in selecting the sample is every kth unit of population is selected, where K is sampling interval, which is calculated as: Sample interval (k)= Total population/sample size 7/21/2016 31

32. This technique leads to more accurate result if the population is homogenous . 7/21/2016 32

33. Stratified sampling This sampling technique is applicable when:- The population is large. The population is not homogenous. First the population is divided into homogenous group called strata, and the sample is drawn from each stratum at random in proportion to its size. This gives greater accuracy result. The demerit of this technique is, dividing the population into homogenous group. 7/21/2016 33

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35. Cluster sampling. Cluster sampling is applicable when preparing the sampling frame is difficult. In it, geographical area is divided into small area called cluster. This technique allows only small number of target population to be sampled. Normally 30 clusters are selected by systematic sampling method. Error will be more but cost of study is reduced. 7/21/2016 35

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37. Judgment Choosing the sample items depends on the judgment of the investigator. Samples are because the investigator believes that they are typical or representative of the population under his/her study. 7/21/2016 37

38. Convenience sampling Selection is made from an available source like that from a nearly college students to study the awareness regarding AIDS in college students, because getting sample is convenient. Non- random sampling is biased and unsatisfactory, but time, cost and resource required will be considerably less. 7/21/2016 38

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40. Quota Sampling 7/21/2016 40 The general composition of the sample is decided in advance. The only requirement is that to find right number of people to somehow fill the quotas. This is generally done to insure the inclusion of a particular segment of the population.

41. Purposive Sampling 7/21/2016 41 A purposive sample is a non-representative subset of some larger population, and is constructed to serve a very specific need or purpose.. A subset of a purposive sample is a snowball sample (chain referral sampling )— so named because one picks up the sample along the way, analogous to snow ball accumulating. s now. A snowball samples is achieved by asking a participant to suggest some one else who might be willing or appropriate for the study.

42. SAMPLING ERROR The occurrence of variation from one sample to another sample is called sampling error. The factors that influence the sampling error are: Size of the sample. Natural variability of the individual reading. As the size of the sample increases, sampling error will decrease. 7/21/2016 42

43. NON-SAMPLING ERROR Sampling error is not only error which arises in a sample survey, error may also occur due to inadequately calibrated instruments. 7/21/2016 43

44. REFERENCES 7/21/2016 44 Hiremath SS. Textbook of preventive and community dentistry. 2 nd edition, 2011. Elseviers Publications. Peter S. Essentials Of Preventive And Community Dentistry.5 TH nd Edition,2014. Arya publications.

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