Cluster sampling cluster sampling is a sampling method where the entire population is divided into groups, or clusters, and a random sample of these clusters are selected. It is useful when the researcher know little about a group or organisation. Sampling methods chapter 4 sampling methods that do not ensure each member of the population has an equal chance of being selected into the study voluntary response samples. Select a sample of n clusters from n clusters by the method of srs, generally wor. The world health organizations who department of immunization, vaccines, and biologicals has long provided guidance on assessing vaccination coverage using both cluster and lot quality assurance sampling lqas survey methods.
Simple random sampling, systematic sampling, stratified sampling fall into the category of simple sampling techniques. Alternative estimation method for a threestage cluster sampling in finite population. This article is on representation of basis and the basis selection of techniques. Download sampling techniques by william g cochran book pdf. Sampling techniques download ebook pdf, epub, tuebl, mobi. For example, in marketing research, the question at hand might be how adolescents react to a particular brand of chewing gum. Quota sampling 3 is a nonprobability sampling technique wherein the researcher ensures equal or proportionate representation of subjects depending on which trait is considered as basis of the quota. Cluster sampling involves identification of cluster of participants representing the population and their inclusion in the sample group. Simple random sampling in an ordered systematic way, e.
Cluster sampling is commonly implemented as multistage sampling. A sampling frame is a list of the actual cases from which sample will be drawn. In twostage cluster sampling, a random sampling technique is applied to the elements from each of the selected clusters. Sampling theory chapter 9 cluster sampling shalabh, iit kanpur page 3 case of equal clusters suppose the population is divided into n clusters and each cluster is of size m. Used when a sampling frame not available or too expensive, and b cost of reaching an individual element is too high. In simple terms, in multistage sampling large clusters of population are divided into smaller clusters in several stages in order to make primary data collection more manageable.
Consider the mean of all such cluster means as an estimator of. Its a sampling method used when assorted groupings are naturally exhibited in a population, making random sampling from those groups. Essentially, each cluster is a minirepresentation of the entire population. Chapter 5 choosing the type of probability sampling 129 respondents may be widely dispersed. Raj, p4 all these four steps are interwoven and cannot be considered isolated from one another. Jan 31, 2014 cluster sampling is commonly implemented as part of multistage cluster sampling, often referred to simply as multistage sampling. For this reason, cluster sampling requires a larger sample than srs to achieve the same level of accuracy but cost savings from clustering might still make this a cheaper option. A variety of sampling strategies are available in cases when setting or context create restrictions. Cluster sampling is commonly implemented as part of multistage cluster sampling, often referred to simply as multistage sampling.
All observations in the selected clusters are included in the sample. Cluster sampling is a probability sampling technique in which all population elements are categorized. Click download or read online button to get sampling techniques book now. We will focus our attention on these three methods. This is a cluster sample, the cluster being the block. For the love of physics walter lewin may 16, 2011 duration. Cluster or multistage sampling cluster sampling is a sampling technique where the entire population is divided into groups, or clusters. This site is like a library, use search box in the widget to get ebook that you want. Cluster sampling definition, advantages and disadvantages.
This is a complex form of cluster sampling in which two or more levels of units are embedded one. Clearly demonstrates a wide range of sampling methods now in use by governments, in business, market and operations research, social science, medicine, public health, agriculture, and accounting. For example, stratified sampling is used when the populations characteristics such as ethnicity or gender are related to the outcome or dependent variables being studied. The 30 by 7 cluster survey is a modified twostage cluster sample and the lqas method is a type of stratified sample. In stratified random sampling, all the strata of the population is sampled while in cluster sampling, the researcher only randomly selects a number of clusters from the collection of clusters of the entire population. For example, if basis of the quota is college year level and the researcher needs equal. Jul 26, 2018 this sampling technique uses randomization to make sure that every element of the population gets an equal chance to be part of the selected sample. Population is divided into geographical clusters some. Description and comparison of the methods of cluster sampling and.
This sampling technique uses randomization to make sure that every element of the population gets an equal chance to be part of the selected sample. Used when a sampling frame not available or too expensive, and. This is population based survey and we used random cluster sampling technique. The sample size is larger the method used to select the sample utilizes a random process nonrandom sampling methods often lead to results that are not representative of the population example. Sampling provides an uptodate treatment of both classical and modern sampling design and estimation methods, along with sampling methods for rare, clustered, and hardtodetect populations. A stratified two stage cluster sampling approach was therefore used to ensure the resulting sample was representative of the country, while concentrating resources in fewer areas a is true. Most researchers are bounded by time, money and workforce and because of these limitations, it is almost impossible to randomly sample the entire population and it is often necessary to employ another sampling technique, the nonprobability sampling technique. The corresponding numbers for the sample are n, m and k respectively.
The sampling frame the sampling frame is the list of ultimate sampling entities, which may be people, households, organizations, or other units of analysis. Multistage sampling also known as multistage cluster sampling is a more complex form of cluster sampling which contains two or more stages in sample selection. Download pdf show page numbers cluster sampling is a probability sampling technique in which all population elements are categorized into mutually exclusive and exhaustive groups called clusters. Cluster sampling also known as onestage cluster sampling is a technique in which clusters of participants that represent the population are identified and included in the sample 1. Cluster sampling a cluster sample is a probability sample in which each sampling unit is a collection or a group of elements. Population divided into different groups from which we sample randomly. A cluster sample is a probability sample in which each sampling unit is a collection or a. The representation of this two is performed either by the method of probability random sampling or by the method of nonprobability random sampling. An example of multistage sampling has been given in a previous question. This approach is ideal only if the characteristic of interest is distributed homogeneously across. Cluster sampling has been described in a previous question.
Rather than listing all elementary school children in a given city and randomly selecting 15 per cent. Freedman department of statistics university of california berkeley, ca 94720 the basic idea in sampling is extrapolation from the part to the. Simple random sampling, in contrast, is used when there is no regard for strata or defining characteristics of the. Insights from an overview of the methods literature abstract the methods literature regarding sampling in qualitative research is characterized by important inconsistencies and ambiguities, which can be problematic for students and researchers seeking a clear and coherent understanding.
In singlestage cluster sampling, all the elements from each of the selected clusters are sampled. The main difference between cluster sampling and stratified sampling lies with the inclusion of the cluster or strata. Then a random sample of these clusters are selected using srs. There are more complicated types of cluster sampling such as twostage cluster. A manual for selecting sampling techniques in research 5 of various types of probability sampling technique. Because a geographically dispersed population can be expensive to survey, greater economy than simple random sampling can be achieved by grouping several respondents within a local area into a cluster. When sampling clusters by region, called area sampling. Cluster sample a sampling method in which each unit selected is a group of persons all persons in a city block, a family, etc. Download sampling techniques by william g cochran book pdf free latest news6 gec multan.
Stratified random sampling the way in which was have selected sample units thus far has required us to know little about the population of interest in advance of selecting the sample. Cluster sampling is the selection of units of natural groupings rather than individuals. In any form of research, true random sampling is always difficult to achieve. One of the advantages of using the cluster sampling is economical in reducing cost by concentrating on the selected clusters it gives less precision than the simple random sampling. After identifying the clusters, certain clusters are chosen using simple. Alternative estimation method for a threestage cluster. This third edition retains the general organization of the two previous editions, but incorporates extensive new materialsections, exercises, and. In statistics, cluster sampling is a sampling method in which the entire population of the study is divided into externally homogeneous, but internally heterogeneous, groups called clusters. In cluster sampling the sample units contain groups of elements clusters instead of individual members or items in the population. A random sampling technique is then used on any relevant clusters to choose which clusters to include in the study. Population is divided into geographical clusters some clusters are chosen. Nov 22, 20 a stratified two stage cluster sampling approach was therefore used to ensure the resulting sample was representative of the country, while concentrating resources in fewer areas a is true. They are also usually the easiest designs to implement. Cluster sampling is one of the efficient methods of random sampling in which the population is first divided into clusters, and then a sample is selected from the clusters randomly.
If only a sample of elements is taken from each selected cluster, the method is known as twostage. Cluster sampling is a statistical sampling technique used when the population cannot be defined as being homogenous, making random sampling from classifications possible. Is an additional progress of the belief that cluster sampling have. To study the consumption pattern of households, the people living in houses, hotels, hospitals, prison etc. To study the consumption pattern of households, the people living in houses, hotels. Appendix iii is presenting a brief summary of various types of nonprobability sampling technique. Researchers then select random groups with a simple random or systematic random sampling technique for data collection and data analysis. Use smaller cluster size in terms of number of householdsindividuals selected in each cluster. Apr 11, 2016 download sampling techniques by william g cochran book pdf free. Gives proofs of all the theoretical results used in modern sampling practice. Sampling methods chapter 4 it is more likely a sample will resemble the population when. Over time, expanded programme on immunization epi coverage surveys have increased in complexity. The interviewer has been given quotas to fill from.
Meant for instructors, graduate college students and survey practitioners, this book addresses in a energetic and progressive approach the methods of sampling, using estimators and the strategies of applicable calibration, and the understanding of issues pertaining to nonresponse. The first two theorems apply to stratified sampling in general and are not restricted to stratified random sampling. A manual for selecting sampling techniques in research. Sampling theory chapter 9 cluster sampling shalabh, iit kanpur page 4 estimation of population mean. Simple random sampling and systematic sampling simple random sampling and systematic sampling provide the foundation for almost all of the more complex sampling designs based on probability sampling. For example, in surveys of internet users it is sometimes useful or convenient to first sample by discussion groups or internet domains, and then to sample individual users within the groups or. New topics in this edition include the approximate methods developed for the problem of attaching standard errors or. Pdf on jan 31, 2014, philip sedgwick and others published cluster. Cluster sampling is a probability sampling technique where researchers divide the population into multiple groups clusters for research. Use a constant take size rather than a variable one say 30 households so in cluster sampling, a. In pure cluster sampling, whole cluster is sampled. Unlike cluster sampling, this method ensures that every high school in nm is represented in the study. Based on n clusters, find the mean of each cluster separately based on all the units in every cluster. Jun 06, 2016 for the love of physics walter lewin may 16, 2011 duration.
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