06-Unit6 - Research Methodology Unit 6 Unit 6 Sampling...

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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 Multi-stage and sub-sampling 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 Non-probability 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 Snow-ball 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 Non-probability 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 non-probability 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, multi-stage 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; multi-stage cluster sampling instead of single-stage 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 non-availability 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 sub-divided 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 sub-populations 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 self-weighing 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 over-representation 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 non-probability 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 time-consuming. 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, socio-economic 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 Multi-stage and sub-sampling In multi-stage 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. Sub-sampling is a part of multi-stage sampling process. In a multi-stage sampling, the sampling in second and subsequent stage frames is called sub-sampling. Sub-sampling 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 multi-stage 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, equal-sized 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 multi-phase sampling. This is also known as sequential sampling, as sub-sampling 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 sub-samples rather than one full sample from a population. All the sub-samples should be drawn using the same sampling technique and each is a self-contained and adequate sample of the population. Replicated sampling can be used with any basic sampling technique: simple or stratified, single or multi-stage 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 Non-probability or Non Random Sampling Non-probability sampling 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. 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 non-availability 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 pre-determined 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 Non-random 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 Snow-ball 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 socio-metric 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 non-zero 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 sub-divided 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. Multi-stage 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 pre-selected larger sample that provided information for improving the final selection. Replicated or interpenetrating sampling involves selection of a certain number of sub-samples rather than one full sample from a population. Non-probability 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 pre-determined 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 non-random. Snow-ball 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 Multi-stage and sub-sampling? 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 Non-probability or non random sampling? 11. What is Purposive (or judgment) sampling? 12. What is Quota sampling? 13. What is Snow-ball 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 ...
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