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. A cluster is a natural grouping of peoplefor example, towns, villages, schools, streets, and households. In a statistical study, a sampling method is how we select members from the population to partake in the research. Sampling is a common practice because its seldom possible to collect data from every person within a group. Using singlestage cluster sampling, the ngo can randomly select towns clusters to form a sample and extend help to the girls deprived of education in those towns. Cluster random sampling is a sampling method in which the population is first divided into clusters a cluster is a heterogeneous subset of the population. A sociologist wants to estimate the average yearly vacation budget for each household in a certain city. A list of all currently enrolled students at unmvalencia is obtained and a table of random numbers is used to select a sample of students example. This is an example of stratified sampling, in which each hospital is a stratum. Convenience sampling is a form of nonprobability sampling that involves selection based on availability, opportunity, or convenience. Using singlestage cluster sampling, the ngo can randomly select towns clusters to form a sample and. Cluster sampling involves identification of cluster of participants representing the population and their inclusion in the sample group.
Another form of cluster sampling is twoway cluster sampling, which is a sampling method that involves separating the population into clusters, then. In multistage sampling, the variance of the estimated quantities depends. An example of single stage cluster sampling an ngo wants to create a sample of girls across 5 neighboring towns to provide education. A read is counted each time someone views a publication summary such as the title, abstract, and list of authors, clicks on a figure, or views or downloads the fulltext. In order to implement multistage cluster sampling, the population must be divided into. Jul 20, 20 stratified sampling enables use of different statistical methods for each stratum, which helps in improving the efficiency and accuracy of the estimation. Random selection of 20 students from class of 50 student. Mar 10, 2020 the pollsters use sampling methods to find a small group of people who are representative of the entire population. But, since quota sampling is a nonprobability sampling technique, there are no rules for formally creating samples.
Cluster sampling is only practical way to sample in. Sampling biostatistics college of public health and. Nov 22, 20 a cluster is a natural grouping of peoplefor example, towns, villages, schools, streets, and households. In simple terms, in multistage sampling large clusters of population are divided into smaller clusters in several stages in order to. When sampling clusters by region, called area sampling. For example, in marketing research, the question at hand might be how adolescents react to a particular brand of chewing gum. A cluster sample is a probability sample in which each sampling unit is a. Select a sample of n clusters from n clusters by the method of srs, generally wor. In example above, all 32 boroughs of the greater london represent the sampling frame for the study. The sampling of clusters in the above study was a two stage process. Use a constant take size rather than a variable one say 30 households so in cluster sampling, a.
Cluster sampling has been described in a previous question. In simple multistage cluster, there is random sampling within each randomly chosen. Ross sample design for educational survey research quantitative research methods. Introduction to cluster sampling twostage cluster sampling. This is an example of cluster sampling, in which the hospitals are the clusters. The standard error of the proportion is the square root of the variance or. Sample design introduction when you have a clear idea of the aims of the survey, the particular data requirements, the degree of accuracy required, and have considered the resources and time available, you are in a position to make a decision on the size and form of the collection. In the first stage, census blocks are randomly selected, while in the second stage, interview locations are randomly. Cluster sampling a population can often be grouped in clusters. Chapter 9 cluster sampling area sampling examples iit kanpur. Two stage sampling subsampling in cluster sampling, all the elements in the selected clusters are surveyed. Alternative estimation method for a threestage cluster. The use of cluster sampling in the trial above facilitated cluster allocationthat is, the allocation of wards rather than of the patients themselves to the intervention or control.
Cluster sampling is a statistical sampling technique used when the population cannot be defined as being homogenous, making random sampling from classifications possible. In probability sampling every member of the population has a known non zero probability of being included in the sample. The main aim of cluster sampling can be specified as cost reduction and increasing the levels of efficiency of sampling. Is also much less expensive to fly to just 10 cities instead of 200 cities. Cluster sampling is a variation of sampling design. The main difference between cluster sampling and stratified sampling lies with the inclusion of the cluster or strata.
Cluster sampling faculty naval postgraduate school. Sampling methods chapter 4 a method that ensures each member of the population has an equal chance of being selected example. Difference between stratified and cluster sampling with. Pdf adaptive cluster sampling is a powerful method for parameter. Probability sampling techniques involve a significant amount of rules that the researcher needs to follow to form samples. Pdf twostage adaptive cluster sampling researchgate. Adewara2 1department of mathematics and statistics, federal university of technology, minna, nigeria 2department of statistics, university of ilorin, ilorin, nigeria email. Aug 19, 2017 there is a big difference between stratified and cluster sampling, that in the first sampling technique, the sample is created out of random selection of elements from all the strata while in the second method, the all the units of the randomly selected clusters forms a sample.
Difference between stratified sampling and cluster sampling. The sociologist marked off the city into 400 blocks and treated them as 400 clusters. 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. Another form of cluster sampling is twoway cluster sampling, which is a sampling method that involves separating the population into clusters, then selecting random samples from those clusters. Cluster sampling a cluster sample is a probability sample in which each sampling unit is a collection or a group of elements. The first stage of cluster sampling involved a random sample of 26 villages within each stratum or region.
For example, going to households where there are people outside or where another interviewee told you to go since they know they would answer. Its a sampling method used when assorted groupings are naturally exhibited in a population, making random sampling from those groups. Multistage sampling represents a more complicated form of cluster sampling in which larger clusters are further subdivided into smaller, more targeted groupings for the purposes of surveying. Example of cluster sampling using a ratio estimator. Despite its name, multistage sampling can in fact be easier to implement and can create a more representative sample of the population than a single. Choose a random sample of 50 nurses from each of the 10 hospitals and interview these 50 10 500 regarding their job satisfaction. In this lesson, you will learn how to use stratified random sampling and when it is most appropriate to use it. There is a big difference between stratified and cluster sampling, that in the first sampling technique, the sample is created out of random selection of elements from all the strata while in the second method, the all the units of. The researcher may access such a population through traditional channels. Alternative estimation method for a threestage cluster sampling in finite population. In singlestage cluster sampling, every element in each cluster selected is used. Munich personal repec archive a manual for selecting sampling techniques in research alvi, mohsin university of karachi, iqra university 23 march 2016 online at mpra paper no. Random cluster sampling 1 done correctly, this is a form of random sampling population is divided into groups, usually geographic or organizational some of the groups are randomly chosen in pure cluster sampling, whole cluster is sampled. Use smaller cluster size in terms of number of householdsindividuals selected in each cluster.
Multistage sampling is a complex form of cluster sampling in which two or more levels of units are embedded one in the other. It will be more convenient and less expensive to sample in clusters than individually. A manual for selecting sampling techniques in research. In twostage cluster sampling, a randomized sampling technique is used for selected clusters to generate information. In contrast, the stratified sampling process and its simpler form as a. An example of cluster sampling is area sampling or geographical cluster sampling.
It is given that there are 3,100 households in the city. Anova table for the population of clusters with equal size. The estimated variance is biased, except if the cluster sizes mi are equal. The estimator has the form of a ratio estimator, therefore the estimated variance of. There are more complicated types of cluster sampling such as twostage cluster. Probability sampling is also called as random sampling or representative sampling. Because a geographically dispersed population can be expensive to survey, greater.
We anticipate a response rate of 80%, in which case 625 households must be. It is used when we dont have any kind of prior information about the target population. The fact that the precision of analyzing one subplot and analyzing four subplots is not very different is probably because of the relatively high intra cluster correlation see spatial autocorrelation and precision. Done correctly, this is a form of random sampling population is divided into groups, usually geographic or organizational some of the groups are randomly chosen in pure cluster sampling, whole cluster is sampled. There are three stages for the application of cluster sampling. Cluster sampling it is one of the basic assumptions in any sampling procedure that the population can be divided into a finite number of distinct and identifiable units, called sampling units. The 30x7 method is an example of what is known as a twostage cluster sample. Cluster sampling is the selection of units of natural groupings rather than individuals. Module 3 unesco international institute for educational planning kenneth n.
Cluster sampling involves obtaining a random sample of. It is an example of twostage sampling or multistage sampling. General guidance for use in public heath assessments select seven interview sites per block. Every element has an equal chance of getting selected to be the part sample. 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. This is a popular method in conducting marketing researches. For cluster sampling, we estimate you will need to have completed interviews from at least 500 wom en of reproductive age. Once youve chosen the cities, might be able to get a reasonably accurate list of all the mechanics in each of those cities. In cluster sampling, first define large clusters of people. 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. Because cluster sampling is less precise than ran dom sampling, we must obtain a larger sample size. The correct form of the proportion equation for a household survey is. The corresponding numbers for the sample are n, m and k respectively. In simple terms, in multistage sampling large clusters of population.