Sampling seminar ppt

SAMPLING
DEPARTMENT OF PUBLIC HEALTH DENTISTRY
GUIDED BY
DR.(PROF) VEERANNA
RAMESH
PRESENTED BY
DR.ANANT KUMAR
PG FIRST YEAR
B.I.D.S.H
2

CONTENTS
 INTRODUCTION
 COMMON TERMINOLOGY IN SAMPLING
 IDEAL REQUIREMENTS OF A SAMPLE
 STAGES OF SELECTION OF SAMPLE
 TYPE OF SAMPLING
 DIFFERENCE B/W PROBABILITY & NON-
PROBABILITY SAMPLING
 SAMPLE SIZE CALCULATION
 ERRORS IN SAMPLING
 CONCLUSION
 REFERENCES
3

Introduction
 A Sample is a part of population, called the ‘Universe’, ‘reference’
or ‘parent’ population.
 A group of sampling unit that forms part of population, generally
selected so as to be representative of the population, whose variables
are under study.
4

Sampling
 Sampling is the process or technique of selecting a sample of appropriate
characteristics and adequate size.
or
 Sampling is a process of selecting a no of individual for a study in such a
way that the individuals represent the larger group from which they were
selected.
5

Common
terminology used
in sampling
6
POPULATION:- A population is a representative sample of a larger group
of people (or even things) with one or more characteristics in common.

COMMON
TERMINOLOGY
USED IN
SAMPLING
7

STAGES IN THE
SELECTION OF
SAMPLE
8
Define the target population
Select a sampling frame
Conduct fieldwork
Determine if a probability or nonprobability sampling
method will be chosen
Plan procedure for selecting sampling units
Determine sample size
Select actual sampling units

Ideal requirements
of a sample
1. Efficiency:- It is the ability of the sample to yield the desired
information.
2. Representativeness:- A sample should be representative of the
parent population so that inferences drawn from the sample can be
generalized to that population with measurable precision and
confidence.
3. Measurability:- The design of the sample should be such that
valid estimates of its variability can be made, that is, the
investigator should be able to estimate the extent to which findings
from the sample are likely to differ from the parent population.
4. Size:- A sample should be large enough to minimize sample
variability and to allow estimates of the population characteristics
to be made with measurable precision.
9

Ideal requirements
of a sample
5. Coverage:- Adequate coverage is essential if the sample has to
remain representative. High rates of refusal / non-response, loss to
follow-up and other missing data can make a sample un representative
of the parent population.
6. Goal orientation:- Sample selection should be oriented towards
the study objectives and research design.
7. Feasibility:- The design should be simple enough to be carried out
in practice.
8. Economy and cost-efficiency:- The sample design should be such
that it should yield the desired information with appreciable savings in
time and cost and with least sampling error.
10

Types
of
sampling
In probability sampling,
each sample has an equal
probability of being chosen.
This method of sampling
gives the probability that
our sample is representative
of a population.
1.
Probability
Sampling
Non-probability sampling
technique uses non-
randomized methods to
draw the sample.
Non-probability sampling
method mostly involves
judgement instead of
randomization, participants
are selected because they
are easy to access.
2. Non –
probability
Sampling
11

Method of probability
sampling
or
random sampling
1. Simple
random
sampling
2. Systematic
sampling
4. Cluster
sampling
5. Multistage
sampling
3. Stratified
random
sampling
12

1. Simple random
sampling
 In this sampling technique each and every unit in the population has an equal
chance of being included in the sample. In this method, the selection of the unit
is determined by chance only.
BASIC PROCEDURE:
 Prepare a sampling frame.
 Decide on the size of the sample.
 Select the required number of units
 To ensure randomness one may choose any one of the following methods:
i) LOTTERY METHOD
ii) TABLE OF RANDOM NUMBERS
13

Methods to apply
simple random
sampling
14

Methods to apply
simple random
sampling
II) TABLE OF RANDOM NUMBERS:-
The table of random numbers consist of random arrangements of digits
from 0 to 100 in rows and columns. The selection is done either in a
horizontal or vertical direction. This method assures randomness and
eliminates personal bias.
15

Simple random
sampling
ADVANTAGE
 Ease of task in smaller populations
 No personal bias.
 Sample more representative of population.
 Accuracy can be assessed as sampling errors follow
principals of chance.
DISADVANTAGE
 Requires completely catalogued universe.
 Subjects too widely dispersed - more time and cost.
16

2. Systematic
sampling
 A systematic sample is obtained by selecting one unit at random and
then selecting additional units at evenly spaced interval till the sample
of required size has been got.
K = Total population/Sample size desired, Where k = sampling interval/fraction.
 For example, to obtain a sample of the patients attending a dental
clinic, suppose there are 30 patients in a clinic and it is decided to
select a sample size 10, then K=30/10 gives quotient 03. (here 3 is my
interval/fraction)
 The first number is selected at random then the next unit will be 3 + 3 = 6.
Hence the serial numbers of the sample will be 3, 6, 9 and so on till 10
numbers/samples are got.
17

Systematic
sampling
ADVANTAGE
 The systematic design is simple, convenient to adopt.
 The time and labor involved in the collection of sample is
relatively small.
 If the population is sufficiently large, homogeneous and each
unit is numbered, this method can yield accurate results.
DISADVANTAGE
 Sample may be biased if hidden periodicity in population
coincides with that of selection.
18

3. Stratified
random sampling
A stratified random sample is obtained using the following
procedure:-
I. The population to be sampled is subdivided into groups known as
strata, such that each group is homogeneous in its characteristic.
II. A simple random sample is then chosen from each stratum. This
type of sampling is used when the population is heterogeneous with
regard to the characteristic under study.
For example, to determine the prevalence of DMF teeth in different age
groups, the different age groups form the strata and a random sample is to
be chosen from each stratum i.e. age group.
19
Below 18
Above 50 Between 18-50

Stratified random
sampling
ADVANTAGE
 Identification of all members of the population can be difficult
 Identifying members of all subgroups can be difficult
DISADVANTAGE
 More accurate sample
 Can be used for both proportional and non-proportional samples
 Representation of subgroups in the sample
20

4. Cluster
sampling
 This method is used when the population forms natural groups or clusters,
such as, villages, wards blocks or children of a school etc.
 Basic procedure:- First a sample of the clusters is selected and then all
the units in each of the selected clusters are surveyed.
 This method is simpler and involves less time and cost, but gives a high
standard error.
21

Cluster sampling
ADVANTAGE
 Very useful when populations are large and spread over a large
geographic region
 Convenient and more time and cost effective.
DISADVANTAGE
 Representation is likely to become an issue
 Standard error is higher
22

5. Multiphase
sampling
 BASIC PROCEDURE:-
 The first stage is to select the groups or clusters then subsamples
are taken in as many subsequent stages as necessary to obtain the
desired sample size.
For example - In TB Survey, MT test for all cases - Phase 1
 Chest X-ray in MT +ve cases - Phase 2
 Sputum examination in X-ray +ve cases – Phase 3
 This method is less costly, less laborious & more purposeful.
*MT= Mantoux test
23

METHOD OF NON-
PROBABILITY
SAMPLING
or
Non-Random sampling
1.
Convenience
sampling
2. Judgemental
or purposive
sampling
4. Quota
sampling
3. Snow ball
sampling
24

1. Convenience
sampling
 In this type of sampling, researchers prefer participants as per their own
convenience. The researcher selects the closest live persons as respondents.
 In convenience sampling, subjects who are readily accessible or available
to the researcher are selected.
 A basic example of a convenience sampling method is when companies
distribute their promotional pamphlets and ask questions at a mall or on a
crowded street with randomly selected participants.
25
RESEARCHER

Advantage and
disadvantage of
convenience
sampling
ADVANTAGE
 Easy method of sampling
 Less time consuming
 Economic way of sampling
DISADVANTAGE
 May not represent the whole population
26

2. Judgemental or
purposive
sampling
 In this type of sampling, the researcher chooses the participants as per
his/her own judgment, keeping back in mind the purpose of the study.
 It uses the judgment of an expert in selecting cases or it selects cases
with a specific purpose in mind.
 This type of sampling is used in exploratory research or in field
research.
27

Advantage&
disadvantageof
purposive
sampling
ADVANTAGE
 Less costly
 More convenient
 Low margin of error
DISADVANTAGE
 Ineffective method when applied to large population
groups.
 No way to evaluate the reliability of the expert.
 Extremely prone to researcher bias.
28

3. Snow ball
sampling
 Also called "chain referral sampling,” in this method, the sample is actually
collected in various stages.
 Snowball sampling is basically sociometric in nature, although this is
considered to be a form of accidental sampling.
 This method is appropriate when the members of a special population are
difficult to locate for example:- Covid 19 cases, homeless people, migrant
workers etc.
29
 Basic procedure:- It begins by the collection of data from one or
more contacts usually known to the person collecting the data. At the
end of the data collection process (e.g., questionnaire, survey, or
interview), the data collector asks the respondent to provide contact
information for other potential respondents.
 These potential respondents are contacted, interviewed and further
asked to provide more contacts. This process goes on till the purpose
of the researcher is achieved.

Advantage&
disadvantageof
snowball
sampling
ADVANTAGE
 The chain referral process allows the researcher to reach
populations that are difficult to sample with other
method.
 Cheap, simple and cost-efficient.
DISADVANTAGE
 First participants will have a strong impact on the
sample.
 Need planning and fewer workforce.
30

4. Quota
sampling
 In this sampling method, we pre-plan the number of participants in specified
categories (For example; 100 literates, 100 illiterate). You select your sample
according to some fixed quota. We allot shares to different groups (for
example 100 men, 100 women).
 This type of sampling method may be further divided into uncontrolled quota
sampling and controlled quota sampling.
 In uncontrolled quota sampling, the researcher selects the sample as per
his/her own convenience. On the other side, some restrictions are imposed to
limit researcher’s choice in controlled quota sampling.
31

Advantage&
disadvantagesof
quotasampling
ADVANTAGE
 A time saving, less costly and easy method with high rate of
accuracy is what always we want in sampling.
 Improves the representation of any particular group within the
population.
 Ensuring that these groups are not over-represented.
DISADVANTAGE
 Impossible to find the sampling error.
 Other issues related with items that can not be clearly
Categorized to certain groups.
32

DIFFERENCE
BETWEEN
PROBABILITY AND
NON-PROBABILITY
METHOD
33

SAMPLE SIZE
CALCULATION
 Bigger the sample, higher will be the precision of the estimates of the sample.
 An optimum size of the sample is to be considered, keeping in mind the
following factors.
 An approximate idea of the estimate of the characteristics under study and its
variability from unit to unit in the population. This may be obtained from
previous investigations or through pilot survey to be conducted immediately :
before the start of the actual investigation.
 Knowledge about the characteristic under study.:-
I. The probability level within which the desired precision is to be maintained.
II. The availability of experimental material, resources and other practical
consideration.
 For instance, if a field survey is conducted to estimate the prevalence rate of a
disease, the sample size is calculated by the formula,
n=4pq/L2
 Where, n is the sample size, p is the approximate prevalence rate of the disease,
q is 1-p and L is the permissible error in the estimation of p.
34

ERRORS
IN
SAMPLING
 There are two types of errors in sampling:-
1. SAMPLING ERROR :- The sampling errors are errors that
creep in due to the sampling process and could arise because of
faulty sample design or due to the small size of the sample.
2. NON-SAMPLING ERROR:-
The non-sampling errors are of following types-
a) Coverage error:- due to non-response or non-cooperation of
the informant.
b) Observational error:- Due to interviewers bias or imperfect
experimental technique or interaction of both.
c) Processing error - due to errors in statistical analysis.
35

Sampling Bias
 Sampling bias:- it is a tendency to favor a selection of sample that
possess particular characteristics. It is a systematic error that leads to
distortion in the result of study. It may occur in the form of over-
representation bias.
 Bias may be un-intentional(accidental/mistake) or intentional.
 Types of sampling bias are as follows:-
1. Self-selection bias/response bias:- this type of bias happen in a
situation when the participants in the study have some control over
the study to participate or not.
2. Household bias:- when one type of respondent it over represented
because groupings(strata) of different sizes are polled equally.
3. Exclusion/non-response bias:- this type of bias happen when some
people of the group are eliminated from the study.
4. Healthy user bias:- this type of bias occurs when the sample selected
has more likelihood to be healthier as compared to general population.
36

CONCLUSION
 A good understanding of sample and sampling techniques is
imperative to conduct any kind of research at study.
 We, as Public Health Dentists; by sharpening our statistical skills can
play a vital role in conducting and analyzing researches and thus
contribute to our highest degree in the field of dental as well as
medical research.
37

REFERENCES
1. Peter Soben, Essentials of Preventive and Community Dentistry, 5th
Edition. Pg no: 590-594
2. Marya CM A Text Book of Public Health Dentistry, 1st Edition. Pg no:
31-33
3. Hu S. (2014) Study Population. In: Michalos A.C. (eds) Encyclopedia
of Quality of Life and Well-Being Research.
https://doi.org/10.1007/978-94-007-0753-5_2893
4. Showkat, Nayeem & Parveen, Huma. (2017). Non-Probability and
Probability Sampling.
38

Sampling seminar ppt

More Related Content

What's hot (20)

Similar to Sampling seminar ppt (20)

Recently uploaded (20)

Sampling seminar ppt