Unformatted text preview: Research Methodology Unit 6 Unit 6 Sampling Structure
6.1 Meaning of sampling
Objectives 6.2 Advantages of sampling 6.3 Sampling procedure 6.4 Characteristics of good sample 6.5 Methods of Sampling
6.5.1 Probability or Random Sampling 6.5.2 Simple Random Sampling 6.5.3 Stratified Random Sampling 6.5.4 Systematic Random Sampling 6.5.5 Cluster Sampling 6.5.6 Area sampling 6.5.7 Multistage and subsampling 6.5.8 Random Sampling with Probability Proportional to Size 6.5.9 Double Sampling and Multiphase Sampling 6.5.10 Replicated or Interpenetrating Sampling
6.5.11 Nonprobability or Non Random Sampling
6.5.12 Convenience or Accidental Sampling
6.5.13 Purposive (or judgment) sampling
6.5.14 Quota sampling
6.5.15 Snowball sampling
Self assessment Questions
6.6 Summary 6.7 Terminal Questions 6.8 Answers to SAQs and TQs Sikkim Manipal University Page No. 68 Research Methodology Unit 6 6.1 Meaning of Sampling
A part of the population is known as sample. The method consisting of the
selecting for study, a portion of the ‘universe’ with a view to draw
conclusions about the ‘universe’ or ‘population’ is known as sampling. A
statistical sample ideally purports to be a miniature model or replica of the
collectivity or the population constituted of all the items that the study should
principally encompass, that is, the items which potentially hold promise of
affording information relevant to the purpose of a given research.
Sampling helps in time and cost saving. It also helps in checking their
accuracy. But on the other hand it demands exercise of great care caution;
otherwise the results obtained may be incorrect or misleading. Objectives
After studying this lesson you should be able to understand: Advantages of sampling Sampling procedure Characteristics of good sample Methods of Sampling Probability or Random Sampling Nonprobability or Non Random Sampling 6.2 Advantage of Sample Survey
Sampling has the following advantages: The size of the population: If the population to be studied is quite
large, sampling is warranted. However, the size is a relative matter.
Whether a population is large or small depends upon the nature of the
study, the purpose for which it is undertaken, and the time and other
resources available for it. Sikkim Manipal University Page No. 69 Research Methodology Unit 6 Amount of funds budgeted for the study: Sampling is opted when the
amount of money budgeted is smaller than the anticipated cost of
census survey. Facilities: The extent of facilities available – staff, access to computer
facility and accessibility to population elements  in another factor to be
considered in deciding to sample or not. When the availability of these
facilities is limited, sampling is preferable. Time: The time limit within the study should be completed in another
important factor to be considered in deciding the question of sample
survey. This, in fact, is a primary reason for using sampling by academic
and marketing researchers. 6.3 Sampling Procedure
The decision process of sampling is complicated one. The researcher has to
first identify the limiting factor or factors and must judiciously balance the
conflicting factors. The various criteria governing the choice of the sampling
technique:
(1) Purpose of the Survey: What does the researcher aim at? If he intends
to generalize the findings based on the sample survey to the population,
then an appropriate probability sampling method must be selected. The
choice of a particular type of probability sampling depends on the
geographical area of the survey and the size and the nature of the
population under study.
(2) Measurability: The application of statistical inference theory requires
computation of the sampling error from the sample itself. Probability
samples only allow such computation. Hence, where the research
objective requires statistical inference, the sample should be drawn by
applying simple random sampling method or stratified random sampling Sikkim Manipal University Page No. 70 Research Methodology Unit 6 method, depending on whether the population is homogenous or
heterogeneous.
(3) Degree of Precision: Should the results of the survey be very precise,
or even rough results could serve the purpose? The desired level of
precision as one of the criteria of sampling method selection. Where a
high degree of precision of results is desired, probability sampling
should be used. Where even crude results would serve the purpose
(E.g., marketing surveys, readership surveys etc) any convenient nonrandom sampling like quota sampling would be enough.
(4) Information about Population: How much information is available
about the population to be studied? Where no list of population and no
information about its nature are available, it is difficult to apply a
probability sampling method. Then exploratory study with nonprobability
sampling may be made to gain a better idea of population. After gaining
sufficient knowledge about the population through the exploratory study,
appropriate probability sampling design may be adopted.
(5) The Nature of the Population: In terms of the variables to be studied,
is the population homogenous or heterogeneous? In the case of a
homogenous population, even a simple random sampling will give a
representative sample. If the population is heterogeneous, stratified
random sampling is appropriate.
(6) Geographical Area of the Study and the Size of the Population: If
the area covered by a survey is very large and the size of the population
is quite large, multistage cluster sampling would be appropriate. But if
the area and the size of the population are small, single stage probability
sampling methods could be used.
(7) Financial resources: If the available finance is limited, it may become
necessary to choose a less costly sampling plan like multistage cluster
Sikkim Manipal University Page No. 71 Research Methodology Unit 6 sampling or even quota sampling as a compromise. However, if the
objectives of the study and the desired level of precision cannot be
attained within the stipulated budget, there is no alternative than to give
up the proposed survey. Where the finance is not a constraint, a
researcher can choose the most appropriate method of sampling that fits
the research objective and the nature of population.
(8) Time Limitation: The time limit within which the research project should
be completed restricts the choice of a sampling method. Then, as a
compromise, it may become necessary to choose less time consuming
methods like simple random sampling instead of stratified sampling/sampling with probability proportional to size; multistage
cluster sampling instead of singlestage sampling of elements. Of
course, the precision has to be sacrificed to some extent.
(9) Economy: It should be another criterion in choosing the sampling
method. It means achieving the desired level of precision at minimum
cost. A sample is economical if the precision per unit cost is high or the
cost per unit of variance is low.
The above criteria frequently conflict and the researcher must balance and
blend them to obtain to obtain a good sampling plan. The chosen plan thus
represents an adaptation of the sampling theory to the available facilities
and resources. That is, it represents a compromise between idealism and
feasibility. One should use simple workable methods instead of unduly
elaborate and complicated techniques 6.4 Characteristics of a Good Sample
The characteristics of a good sample are described below: Representativeness: a sample must be representative of the
population. Probability sampling technique yield representative sample. Sikkim Manipal University Page No. 72 Research Methodology Unit 6 Accuracy: accuracy is defined as the degree to which bias is absent
from the sample. An accurate sample is the one which exactly
represents the population. Precision: the sample must yield precise estimate. Precision is
measured by standard error. Size: a good sample must be adequate in size in order to be reliable. 6.5 Methods of Sampling
Sampling techniques or methods may be classified into two generic types:
6.5.1 Probability or Random Sampling
Probability sampling is based on the theory of probability. It is also known as
random sampling. It provides a known nonzero chance of selection for each
population element. It is used when generalization is the objective of study,
and a greater degree of accuracy of estimation of population parameters is
required. The cost and time required is high hence the benefit derived from
it should justify the costs.
The following are the types of probability sampling:
i. Simple Random Sampling: This sampling technique gives each
element an equal and independent chance of being selected. An equal
chance means equal probability of selection. An independent chance
means that the draw of one element will not affect the chances of other
elements being selected. The procedure of drawing a simple random
sample consists of enumeration of all elements in the population.
1. Preparation of a List of all elements, giving them numbers in serial
order 1, 2, B, and so on, and
2. Drawing sample numbers by using (a) lottery method, (b) a table of
random numbers or (c) a computer. Sikkim Manipal University Page No. 73 Research Methodology Unit 6 Suitability: This type of sampling is suited for a small homogeneous
population.
Advantages: The advantage of this is that it is one of the easiest
methods, all the elements in the population have an equal chance of
being selected, simple to understand, does not require prior
knowledge of the true composition of the population.
Disadvantages: It is often impractical because of nonavailability of
population list or of difficulty in enumerating the population, does not
ensure proportionate representation and it may be expensive in time
and money. The amount of sampling error associated with any sample
drawn can easily be computed. But it is greater than that in other
probability samples of the same size, because it is less precise than
other methods.
ii. Stratified Random Sampling: This is an improved type of random or
probability sampling. In this method, the population is subdivided into
homogenous groups or strata, and from each stratum, random sample
is drawn. E.g., university students may be divided on the basis of
discipline, and each discipline group may again be divided into juniors
and seniors. Stratification is necessary for increasing a sample’s
statistical efficiency, providing adequate data for analyzing the various
subpopulations and applying different methods to different strata. The
stratified random sampling is appropriate for a large heterogeneous
population. Stratification process involves three major decisions. They
are stratification base or bases, number of strata and strata sample
sizes.
Stratified random sampling may be classified into:
a) Proportionate stratified sampling: This sampling involves
drawing a sample from each stratum in proportion to the latter’s
share in the total population. It gives proper representation to each
Sikkim Manipal University Page No. 74 Research Methodology Unit 6 stratum and its statistical efficiency is generally higher. This
method is therefore very popular. E.g., if the Management Faculty
of a University consists of the following specialization groups:
Specialization stream No. of students Proportion of each
stream Production 40 0.4 Finance 20 0.2 Marketing 30 0.3 Rural development 10 0.1 100 1.0 The research wants to draw an overall sample of 30. Then the
strata sample sizes would be:
Strata Sample size Production 30 x 0.4 12 Finance 30 x 0.2 6 Marketing 30 x 0.3 9 Rural development 30 x 0.1 3
30 Advantages: Stratified random sampling enhances the representativeness to each sample, gives higher statistical
efficiency, easy to carry out, and gives a selfweighing sample.
Disadvantages: A prior knowledge of the composition of the population and the distribution of the population, it is very
expensive in time and money and identification of the strata may
lead to classification of errors.
Sikkim Manipal University Page No. 75 Research Methodology Unit 6 b) Disproportionate stratified random sampling: This method
does not give proportionate representation to strata. It necessarily
involves giving overrepresentation to some strata and underrepresentation to others. The desirability of disproportionate
sampling is usually determined by three factors, viz, (a) the sizes
of strata, (b) internal variances among strata, and (c) sampling
costs.
Suitability: This method is used when the population contains
some small but important subgroups, when certain groups are
quite heterogeneous, while others are homogeneous and when it
is expected that there will be appreciable differences in the
response rates of the subgroups in the population.
Advantages: The advantages of this type is it is less time
consuming and facilitates giving appropriate weighing to particular
groups which are small but more important.
Disadvantages: The disadvantage is that it does not give each
stratum proportionate representation, requires prior knowledge of
composition of the population, is subject to classification errors and
its practical feasibility is doubtful.
iii. Systematic Random Sampling: This method of sampling is an
alternative to random selection. It consists of taking kth item in the
population after a random start with an item form 1 to k. It is also
known as fixed interval method. E.g., 1st, 11th, 21st ……… Strictly
speaking, this method of sampling is not a probability sampling. It
possesses characteristics of randomness and some nonprobability
traits.
Suitability: Systematic selection can be applied to various populations
such as students in a class, houses in a street, telephone directory etc.
Sikkim Manipal University Page No. 76 Research Methodology Unit 6 Advantages: The advantages are it is simpler than random sampling,
easy to use, easy to instruct, requires less time, it’s cheaper, easier to
check, sample is spread evenly over the population, and it is
statistically more efficient.
Disadvantages: The disadvantages are it ignores all elements
between two k th elements selected, each element does not have equal
chance of being selected, and this method sometimes gives a biased
sample.
6.5.5 Cluster Sampling
It means random selection of sampling units consisting of population
elements. Each such sampling unit is a cluster of population elements. Then
from each selected sampling unit, a sample of population elements is drawn
by either simple random selection or stratified random selection. Where the
population elements are scattered over a wide area and a list of population
elements is not readily available, the use of simple or stratified random
sampling method would be too expensive and timeconsuming. In such
cases cluster sampling is usually adopted. The cluster sampling process
involves: identify clusters, examine the nature of clusters, and determine the
number of stages.
Suitability: The application of cluster sampling is extensive in farm
management surveys, socioeconomic surveys, rural credit surveys,
demographic studies, ecological studies, public opinion polls, and large
scale surveys of political and social behaviour, attitude surveys and so on.
Advantages: The advantages of this method is it is easier and more
convenient, cost of this is much less, promotes the convenience of field
work as it could be done in compact places, it does not require more time,
units of study can be readily substituted for other units and it is more
flexible.
Sikkim Manipal University Page No. 77 Research Methodology Unit 6 Disadvantages: The cluster sizes may vary and this variation could
increase the bias of the resulting sample. The sampling error in this method
of sampling is greater and the adjacent units of study tend to have more
similar characteristics than do units distantly apart.
6.5.6 Area sampling
This is an important form of cluster sampling. In larger field surveys cluster
consisting of specific geographical areas like districts, talluks, villages or
blocks in a city are randomly drawn. As the geographical areas are selected
as sampling units in such cases, their sampling is called area sampling. It is
not a separate method of sampling, but forms part of cluster sampling.
6.5.7 Multistage and subsampling
In multistage sampling method, sampling is carried out in two or more
stages. The population is regarded as being composed of a number of
second stage units and so forth. That is, at each stage, a sampling unit is a
cluster of the sampling units of the subsequent stage. First, a sample of the
first stage sampling units is drawn, then from each of the selected first stage
sampling unit, a sample of the second stage sampling units is drawn. The
procedure continues down to the final sampling units or population
elements. Appropriate random sampling method is adopted at each stage. It
is appropriate where the population is scattered over a wider geographical
area and no frame or list is available for sampling. It is also useful when a
survey has to be made within a limited time and cost budget. The major
disadvantage is that the procedure of estimating sampling error and cost
advantage is complicated.
Subsampling is a part of multistage sampling process. In a multistage
sampling, the sampling in second and subsequent stage frames is called
subsampling. Subsampling balances the two conflicting effects of
clustering i.e., cost and sampling errors.
Sikkim Manipal University Page No. 78 Research Methodology Unit 6 6.5.8 Random Sampling with Probability Proportional to Size
The procedure of selecting clusters with probability Proportional to size
(PPS) is widely used. If one primary cluster has twice as large a population
as another, it is give twice the chance of being selected. If the same number
of persons is then selected from each of the selected clusters, the overall
probability of any person will be the same. Thus PPS is a better method for
securing a representative sample of population elements in multistage
cluster sampling.
Advantages: The advantages are clusters of various sizes get proportionate representation, PPS leads to greater precision than would a
simple random sample of clusters and a constant sampling fraction at the
second stage, equalsized samples from each selected primary cluster are
convenient for field work.
Disadvantages: PPS cannot be used if the sizes of the primary sampling
clusters are not known.
6.5.9 Double Sampling and Multiphase Sampling
Double sampling refers to the subsection of the final sample form a preselected larger sample that provided information for improving the final
selection. When the procedure is extended to more than two phases of
selection, it is then, called multiphase sampling. This is also known as
sequential sampling, as subsampling is done from a main sample in
phases. Double sampling or multiphase sampling is a compromise solution
for a dilemma posed by undesirable extremes. “The statistics based on the
sample of ‘n’ can be improved by using ancillary information from a wide
base: but this is too costly to obtain from the entire population of N
elements. Instead, information is obtained from a larger preliminary sample
nL which includes the final sample n. Sikkim Manipal University Page No. 79 Research Methodology Unit 6 6.5.10 Replicated or Interpenetrating Sampling
It involves selection of a certain number of subsamples rather than one full
sample from a population. All the subsamples should be drawn using the
same sampling technique and each is a selfcontained and adequate
sample of the population. Replicated sampling can be used with any basic
sampling technique: simple or stratified, single or multistage or single or
multiphase sampling. It provides a simple means of calculating the sampling
error. It is practical. The replicated samples can throw light on variable nonsampling errors. But disadvantage is that it limits the amount of stratification
that can be employed.
6.5.11 Nonprobability or Non Random Sampling
Nonprobability sampling or nonrandom sampling is not based on the
theory of probability. This sampling does not provide a chance of selection
to each population element.
Advantages: The only merits of this type of sampling are simplicity,
convenience and low cost.
Disadvantages: The demerits are it does not ensure a selection chance to
each population unit. The selection probability sample may not be a
representative one. The selection probability is unknown. It suffers from
sampling bias which will distort results.
The reasons for usage of this sampling are when there is no other feasible
alternative due to nonavailability of a list of population, when the study does
not aim at generalizing the findings to the population, when the costs
required for probability sampling may be too large, when probability
sampling required more time, but the time constraints and the time limit for
completing the study do not permit it. It may be classified into: Sikkim Manipal University Page No. 80 Research Methodology Unit 6 6.5.12 Convenience or Accidental Sampling
It means selecting sample units in a just ‘hit and miss’ fashion E.g.,
interviewing people whom we happen to meet. This sampling also means
selecting whatever sampling units are conveniently available, e.g., a teacher
may select students in his class. This method is also known as accidental
sampling because the respondents whom the researcher meets accidentally
are included in the sample.
Suitability: Though this type of sampling has no status, it may be used for
simple purposes such as testing ideas or gaining ideas or rough impression
about a subject of interest.
Advantage: It is the cheapest and simplest, it does not require a list of
population and it does not require any statistical expertise.
Disadvantage: The disadvantage is that it is highly biased because of
researcher’s subjectivity, it is the least reliable sampling method and the
findings cannot be generalized.
6.5.13 Purposive (or judgment) sampling
This method means deliberate selection of sample units that conform to
some predetermined criteria. This is also known as judgment sampling.
This involves selection of cases which we judge as the most appropriate
ones for the given study. It is based on the judgement of the researcher or
some expert. It does not aim at securing a cross section of a population.
The chance that a particular case be selected for the sample depends on
the subjective judgement of the researcher.
Suitability: This is used when what is important is the typicality and specific
relevance of the sampling units to the study and not their overall
representativeness to the population. Sikkim Manipal University Page No. 81 Research Methodology Unit 6 Advantage: It is less costly and more convenient and guarantees inclusion
of relevant elements in the sample.
Disadvantage: It is less efficient for generalizing, does not ensure the
representativeness, requires more prior extensive information and does not
lend itself for using inferential statistics.
6.5.14 Quota sampling
This is a form of convenient sampling involving selection of quota groups of
accessible sampling units by traits such as sex, age, social class, etc. it is a
method of stratified sampling in which the selection within strata is nonrandom. It is this Nonrandom element that constitutes its greatest
weakness.
Suitability: It is used in studies like marketing surveys, opinion polls, and
readership surveys which do not aim at precision, but to get quickly some
crude results.
Advantage: It is less costly, takes less time, non need for a list of
population, and field work can easily be organized.
Disadvantage: It is impossible to estimate sampling error, strict control if
field work is difficult, and subject to a higher degree of classification.
6.5.15 Snowball sampling
This is the colourful name for a technique of Building up a list or a sample of
a special population by using an initial set of its members as informants.
This sampling technique may also be used in sociometric studies.
Suitability: It is very useful in studying social groups, informal groups in a
formal organization, and diffusion of information among professional of
various kinds.
Advantage: It is useful for smaller populations for which no frames are
readily available.
Sikkim Manipal University Page No. 82 Research Methodology Unit 6 Disadvantage: The disadvantage is that it does not allow the use of
probability statistical methods. It is difficult to apply when the population is
large. It does not ensure the inclusion of all the elements in the list.
Self Assessment Questions
1. A sample must be representative of the population. 2.  Probability sampling technique yield representative sample.
3.  accuracy is defined as the degree to which bias is
absent from the sample. An accurate sample is the one which exactly
represents the population.
4. Precision is measured by standard error.
5. A good sample must be adequate in size in order to be
reliable 6.6 Summary
A statistical sample ideally purports to be a miniature model or replica of the
collectivity or the population. Sampling helps in time and cost saving. If the
population to be studied is quite large, sampling is warranted. However, the
size is a relative matter. The decision regarding census or sampling
depends upon the budget of the study. Sampling is opted when the amount
of money budgeted is smaller than the anticipated cost of census survey.
The extent of facilities available – staff, access to computer facility and
accessibility to population elements  is another factor to be considered in
deciding to sample or not. In the case of a homogenous population, even a
simple random sampling will give a representative sample. If the population
is heterogeneous, stratified random sampling is appropriate. Probability
sampling is based on the theory of probability. It is also known as random Sikkim Manipal University Page No. 83 Research Methodology Unit 6 sampling. It provides a known nonzero chance of selection for each
population element.
Simple random sampling technique gives each element an equal and
independent chance of being selected. An equal chance means equal
probability of selection.
Stratified random sampling is an improved type of random or probability
sampling. In this method, the population is subdivided into homogenous
groups or strata, and from each stratum, random sample is drawn.
Proportionate stratified sampling involves drawing a sample from each
stratum in proportion to the latter’s share in the total population.
Disproportionate stratified random sampling does not give proportionate
representation to strata.
Systematic random sampling method is an alternative to random
selection. It consists of taking kth item in the population after a random start
with an item form 1 to k. It is also known as fixed interval method.
Cluster sampling means random selection of sampling units consisting of
population elements.
In Area sampling larger field surveys cluster consisting of specific
geographical areas like districts, taluks, villages or blocks in a city are
randomly drawn.
Multistage sampling is carried out in two or more stages. The population
is regarded as being composed of a number of second stage units and so
forth. That is, at each stage, a sampling unit is a cluster of the sampling
units of the subsequent stage. Sikkim Manipal University Page No. 84 Research Methodology Unit 6 Double sampling and multiphase sampling refers to the subsection of the
final sample form a preselected larger sample that provided information for
improving the final selection.
Replicated or interpenetrating sampling involves selection of a certain
number of subsamples rather than one full sample from a population.
Nonprobability or non random sampling is not based on the theory of
probability. This sampling does not provide a chance of selection to each
population element.
Purposive (or judgment) sampling method means deliberate selection of
sample units that conform to some predetermined criteria. This is also
known as judgment sampling.
Quota sampling is a form of convenient sampling involving selection of
quota groups of accessible sampling units by traits such as sex, age, social
class, etc. it is a method of stratified sampling in which the selection within
strata is nonrandom.
Snowball sampling is the colourful name for a technique of Building up a
list or a sample of a special population by using an initial set of its members
as informants. 6.7 Terminal Questions
1. What is the significance of Sampling in research?
2. Distinguish between Census and sample survey
3. Explain the Sampling process
4. How is Sample size determined?
5. What are the types of Probability or random sampling?
6. Explain Multistage and subsampling?
7. What is Random sampling with probability proportional to size?
8. Distinguish between Double sampling and multiphase sampling
Sikkim Manipal University Page No. 85 Research Methodology Unit 6 9. What is replicated or interpenetrating sampling?
10. What is Nonprobability or non random sampling?
11. What is Purposive (or judgment) sampling?
12. What is Quota sampling?
13. What is Snowball sampling? 6.8 Answers SAQs and TQs
SAQs
1. Representative
2. Probability sampling
3. Accuracy
4. Standard error.
5. Size
TQs
1. Section 6.1
2. Section 6.1
3. Section 6.3
4. Section 6.5.3
5. Section6.51 to Section 6.510
6. Section 6.5.7
7. Section 6.5.8
8. Section 6.5. 9
9. Section 6.5.10
10. Section 6.5.11
11. Section 6.5.13
12. Section 6.5.14
13. Section .5 15 Sikkim Manipal University Page No. 86 ...
View
Full Document
 Spring '10
 smu
 random sampling, Sikkim Manipal University, Multiphase Sampling

Click to edit the document details