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Principle and method for the collection of presentation ,analysis and interpretation of numerical data of different kinds
1)observational data, quantitative data2)data that have been obtained by a
repetitive operation 3)data affected to a marked degree of
a marked degree of a multiplicity of causes
DATA
USES OF STATISTICS IN DENTAL SCINCES ARE AS FOLLOWS:
TO indicate the state of oral health in he community and to determine the availability and utilization of dental care facilities.
To indicate the basic factor underlying the state of oral health by diagnosing the community and solution to such problem.
To promote health legislation and in creating administrative standards for oral health.
To determine success or failure of specific oral health care programs or to evaluate the programmed action.
WHY STATISTIC While conducting and oral health examination
the investigator makes observation according to his judgment of the situation. This depends on his skill, knowledge, experience and temperament. Grading of plaque score or malocclusion or the quantity of diet are situation, which are influenced by the particular investigator who makes the observations. If the same observer repeat the observation on the same case after some time lapse, he may or may not agree with his previous assessment.
Similarly if more than on investigator observes the
same individual all of them may not agree in their
assessment. This variability in measurement can be handled using statistics.
Data
A collective recording of observation either numerical or other wise its called data.
These observation may be collected in a simple way like recording the sex of person in a community or noting down the number of cases of an oral disease in a community or maybe done through an experiment such as finding shear bond of cementum.
VARIABLE
A certain observation is made of characteristic which varies from one person to the other person is called variable
TYPES OF DATA ON THE BASIS OF NATURE OF VARIABLE
QUALITATIVE DATA: When data is collected on the basis of attributes or qualities like sex, malocclusion, cavity etc is called qualitative data.
QUANTITATIVE DATA: when the data is collected through measurement using calipers like arc length arc width fluoride concentration in water supply etc. is called quantitative data.
Quantitative data can be classified in 2 kinds as DISCRETE AND CONTINUOUS
DISCRETE: When the variable under observation takes only fixed value like whole numbers, the data is discrete e.g. the DMF teeth
CONTINUOUS DATA: If the data can take any value in a given range, decimal or fractional is called continuous data like arc length
SOURCES OF DATA ARE:
SURVEYS EXPERIMENTS RECORDS IN OPD OF DENTAL CLINICS
DATA CAN BE COLLECTED EITHER THROUGH
PRIMARY SOURCE
SECONDRY SOURCE
PRIMARY SOURCE: The data is obtained directly by the investigator himself. This is first hand information
SECONDARY SOURCE: The data is already recorded to serve the purpose of the objective of the study. e.g. the record of opd of dental clinics.
Primary data can be obtained using anyone of the following methods
Direct personal interview
Oral health examination
Questionnaire method
DIRECT PERSONAL INTERVIEWS
In this method there is face to face contact with the person from whom the information is to be obtained (called as informants) this method enables to measure subjective phenomena such as the oral health status the opinions, beliefs and attitudes and some behaviourial characteristics.
The advantage of this method is that all the information can be collected accurately and any ambiguity can be clarified. Thus method can not be used when the study is extensive because it is a time consuming and require more personal.
ORAL HEALTH EXAMINATION:
When information is needed on the oral disease, this method provides the more valid information than health interview.
QUESTIONNAIRE METHOD: In this method, a list of question pertaining
to the survey-known as questionnaire is prepared and the varies informants are requested to supply information either personally or through past.
The question should be short easy to understand. There should be no ambiguity while answering the question.
POPULATION
The group of all individual who are the focus of the investigation is known as population. e.g. if it decided to get the prevalence of the DMF teeth in school children then all the children of the school form the population.
CENSUS ENUMERATION
If the information is obtained from each n every individual in the population then it is called census enumeration.
SAMPLE
The word sample means the group of individual who are actually available for the investigation. The sample is the portion of population selected from a population in some manner.
Aim of sample is to get information on a larger group or population. The logical first step in any study is to define population of interest. (target population)
The next step is to list all the individual in that
population as a prelude to select a sample for a detail study.
SAMPLING UNITS
The individual entities that from the focus of study are termed as sampling units.
SAMPLING FRAME
The list of sampling unit is known as sampling frame.
Sample selection can be done in two ways :
1) Purposive selection: The selection of a sample primarily aims at representing the population as a whole. Hence, there can be a great temptation to deliberately or purposively select the individual who seems to represent the population under study
2) Random selection: Here a sample of unit is selected in such a way that all the characteristic of the population is reflected in the sample . This is possible by the selecting unit of sample at random
APPILICATION OF SAMPLING IN COMMUNITY DENTISTRY ARE:
A evaluation of oral health status of a community
B evaluation of health education on oral hygineC studies on administrative aspect of the
service like availability and utilization of oral health facilities in the community.
SAMPLING DESIGN
Different sampling design are available depending upon the type and nature of the population and the objectives of the investigations. Some design commonly used are :
(a) Simple random sampling (b) Systemic random sampling(c) Stratified random sampling(d) Cluster random sampling(e) Multiphase sampling(f) Path finder survey
SIMPLE RANDOM SAMPLING
This is a sampling technique in which each n every unit in the population has an equal chance of being included in the sample. In this method the selection of unit is determined by chance only
(a) Lottery method
(b) Table of random number
(b) SYSTEMIC RANDOM SAMPLING
A systemic sample is formed by selecting one unit at random and than selecting additional unit at evenly spaced interval till the sample of required size has been formed. This method is used when a complete list of population is available.
(C) STRATIFIED RANDOM SAMPLING
The population to be sample is sub divided into groups known as strata, such that each group is homogeneous in its characteristic.
A simple random is than chosen from each stratum this type of sampling is used when the population is heterogeneous with regard to the characteristic under study.
(D) CLUSTER SAMPLING
This method is used when the population forms natural group or cluster such as village, children of school here first a sample of the cluster is selected and then all the unit each of the selected cluster are surveyed.
(E) MULTIPHASE SAMPLING
This method a part of information is collected from the whole sample and a part from the sub-sample.
(F) PATH FINDER SURVEY Some time there is need to sample a
specified proportion of the population say 1% in order to estimate disease prevalence accurately,
This method used is a stratified cluster sampling technique which include the most important population subgroups like to have differing disease level and to cover a standard number of subjects in specific index age group in this way statistically significant and clinically relevant information for planning is obtained of at minimum experience.
This method is suitable for the following situation.
1. The over all prevalence of the various oral disease affecting the population.
2. Important variation in disease level severity and need for treatment subgroups of the population this enables groups in special needs of high priority development of science to be identified.
SAMPLE SIZE
A common question while condecting an investigation is about the size of the sample because the sample higher will be the precision of the estimates of the sample is to be considered keeping in mind the following factor.
1. An approximate idea of the estimates of the characteristic under study and its variability from unit to unit in the population. This may be obtained from previous investigation conducted immediately before the start of actual investigation.
2. Knowledge about the precision of the estimates of the characteristic.
3.The probability level with in which the desired precision is to be maintained..
4.The availability of experimental material, resources and other practical consideration.
For instance in a filed survey is to be conducted to estimate the prevalence rate of a disease the sample size is calculated by the formula-
Where n is the sample size, p approximate prevalence rate of disease ,l is the permissible error in the estimation of p and za is the normal value for the probability level
ERROR IN SAMPLING
Sampling error occurs due to (A) Faulty sampling design (B) Small size of sample
Non sampling error (A) Coverage error: due to non response or
non corporation of the informant (B) Observational error: due to interviewer
bias or imperfect experimental technique.
Processing error: due to error in statistical analysis
PRESENTATION OF DATA
There are two main categories of presentation of data
(a) Tabulation (b) Diagram
Tabulation:
Broadly, the data can be classified on the following bases:
(a) geographical, i.e., area wise, e.g. cities, districts
(b) chronological, i.e., on the basis of time
(c) qualitative, i.e., according to some attribute
(d) quantitative, i.e., in terms of magnitude
The two element of classification are: (a) frequency (b) variable Frequency is the number of units belonging
to each group of variable. A commonest way of presenting data in the table is known as frequency distribution table. The variable characteristic such as age, arch dimension, fluoride concentration in water supply has a range from lowest to highest. This range is divided into subgroup called classes.The class limits are the lowest and highest value that can be included in the class
While forming a frequency distribution table the following basic rules are to be followed
(a) Every table should contain a little as to what is depicted in the table
(b) The number of classes intervals should be too many or too less. It may be preferably between 5 and 20
(c) The class interval should be at equal width
(d) Unit of measurement should be specified
The class limit should be clearly defined to avoid ambiguity. for e.g. 0-4, 5-9,10-14,etc.
Each row and column should be clearly defined with the heading for each row and column.
(B) DIAGRAMS
By arranging the data into tables, we simplify the entire mass of data. But sometimes it is difficult to understand and compare two or more tables . Diagrams and graphs are one of the most convincing and appealing ways of depicting statistical results. diagrams and graphs are extremely useful because they are attractive to eyes, have lasting impression on the mind of the layman and they facilitate comparison of data relating to different time periods and region
TYPES OF DIAGRAMS
Depending on the nature of data, whether it is qualitative or quantitative, any one of the following diagram may be chosen :
(a) Bar diagram: this diagram is used to represent qualitative data. It represent only one variable. For example, the number of the people with D,M,F teeth in a particular age group may be shown by a bar diagram
ILLUSTRATION: Following table gives the D,M , F ,and teeth for individuals aged 15-24 years.
Tooth status No. of individuals D 10 M 18 F 12 DMF 10
(b) MULTIPLE BAR:
This diagram is used to compare qualitative data with respect to a single variable, like sex wise or with respect to time or region.
Illustration 2 YEAR Rural URBAN 1994 124 87 1995 109 72 1996 97 70 TOTAL 330 229
(c) Proportional bar diagram:
This diagram use to represent qualitative data when it is desired to compare only the proportion of subgroup between different major group of observation. The bars are drawn for each group with the same length either as 1% or 100% . These are then divided according to the subgroup proportion in each major group.
(D) Pie diagram:
These are popularly used to show percentage breakdown for qualitative data. It is so called because the entire graph look like a pie and its component represent slices cut from a pie. A circle is divided into different sector corresponding to the frequency of the variable in the distribution.
(E) component bar diagram: This diagram is used to represent
qualitative data. When it is desire to represent both the number of cases major groups as well as subgroups simultaneously we use the component bar diagram. First we draw the rectangle proportional to the number of cases of major group then each rectangle Is divided into the subgroups.
(F) Line diagram This diagram is use to study changes of value in the variable over time and is the simplest type of diagram on the X axis the time such as hours, days, weeks, months, years are represented in the value of any quantity pertaining to this is represent along Y axis
Following are the number of patient at the OPD of dental clinic for one year:
year no. of patient in OPD 1983 554 1984 580 1985 560 1986 604 1987 500 1988 300 1989 230
(G) Histogram
This diagram use to depict quantitative data of continuous type. Histogram is a bar diagram without gape between the bars. It represent the frequency distribution.
following is the frequency distribution of fluoride concentration in parts per million for the water supply of 25 communities.
class interval frequency 0.2-0.3 1 0.4-0.5 1 0.6-0.7 1 0.8-0.9 5 1.0-1.1 10 1.2-1.3 4 total 22
(H) Frequency polygon:
This is used to represent frequency distribution of qualitative data and it is used to compare two or more frequency distribution.
(I) CATOGRAMS OR SPOT MAP:
These are used to show geographical distribution of frequencies of a characteristic.
