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Topic: Stratified sampling

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Cluster sampling

Nonprobability sampling

Systematic sampling

Multistage sampling

Survey sampling

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Importance sampling

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	Statistics Glossary - sampling
		Random sampling is a sampling technique where we select a group of subjects (a sample) for study from a larger group (a population).
		Stratified sampling techniques are generally used when the population is heterogeneous, or dissimilar, where certain homogeneous, or similar, sub-populations can be isolated (strata).
		Sampling variability refers to the different values which a given function of the data takes when it is computed for two or more samples drawn from the same population.
	www.stats.gla.ac.uk /steps/glossary/sampling.html (1219 words)

	Stratified sampling - Wikipedia, the free encyclopedia
		In statistics, stratified sampling is a method of sampling from a population.
		Proportionate allocation uses a sampling fraction in each of the strata that is proportional to that of the total population.
		sampling equal numbers from strata varying widely in size may be used to equate the statistical power of tests of differences between strata.
	en.wikipedia.org /wiki/Stratified_sampling (536 words)

	Cluster sampling - Wikipedia, the free encyclopedia
		The main difference between cluster sampling and stratified sampling is that in cluster sampling the cluster is treated as the sampling unit so analysis is done on a population of clusters (at least in the first stage).
		In stratified sampling, a random sample is drawn from each of the strata, whereas in cluster sampling only the selected clusters are studied.
		The main objective of cluster sampling is to reduce costs by increasing sampling efficiency (This contrasts with stratified sampling where the main objective is to increase precision.).
	en.wikipedia.org /wiki/Cluster_sampling (444 words)

	Regional Sampling Methods
		Stratified sampling is often used when the sampling population can be split into non-overlapping strata that individually are more homogeneous than the population as a whole.
		Stratified sampling is most successful when the variance within each stratum is less than the overall variance of the population.
		The interval (k) depends on the sample size and is determined by the equation i = N/n where N = population size and n = sample size.
	ewr.cee.vt.edu /environmental/teach/smprimer/design/sample.html (795 words)

	Statistics Glossary - Sampling
		Random sampling is a sampling technique where we select a group of subjects (a sample) for study from a larger group (a population).
		When we sample a population with several strata, we generally require that the proportion of each stratum in the sample should be the same as in the population.
		Stratified sampling techniques are generally used when the population is heterogeneous, or dissimilar, where certain homogeneous, or similar, sub-populations can be isolated (strata).
	www.cas.lancs.ac.uk /glossary_v1.1/samp.html (1270 words)

	Learning Resources: Statistics: Power from Data! Probability sampling
		Probability sampling requires that each member of the survey population have a chance of being included in the sample, but it does not require that this chance be the same for everyone.
		Stratifying your list by province, again assuming that this information is available, and then selecting a sample size for each province would allow you to decide on the exact sample size needed for that specific province.
		Multi-stage sampling is like the cluster method, except that it involves picking a sample from within each chosen cluster, rather than including all units in the cluster.
	www.statcan.ca /english/edu/power/ch13/probability/probability.htm (4444 words)

	Sampling
		The goals of sampling are to use a procedure that is likely to yield a “representative” sample of the population as a whole (i.e., to limit exposure to sampling error), while holding down sampling costs as much as possible.
		The three most-commonly-used methods for collecting sample data (when the goal of a study is to estimate means and proportions) are simple random sampling, stratified sampling, and cluster sampling.
		Typical reasons for this are to control for expected differences between the groups (for example, sampling from the pools of men and women separately, in proportion to their representation in the population, if we expect the characteristic being studied to be distributed differently for men than for women).
	www.kellogg.northwestern.edu /faculty/weber/emp/Sampling.htm (1978 words)

	Survey Sampling Methods
		Stratified sampling is often used when one or more of the stratums in the population have a low incidence relative to the other stratums.
		Quota sampling is the nonprobability equivalent of stratified sampling.
		Like stratified sampling, the researcher first identifies the stratums and their proportions as they are represented in the population.
	www.statpac.com /surveys/sampling.htm (742 words)

	DQO - Data Quality Objectives
		Then the total number of samples to be taken are allocated to the strata according to the relative sizes of the strata and the estimated variance in each stratum.
		This is similar to a stratified sampling approach in that samples are distributed according to local variance.
		In a true stratified sampling approach, the goal is to allocate samples among sub-regions (strata) of the decision unit, but make our decision for the whole decision unit (all strata taken as a whole), not for individual strata.
	dqo.pnl.gov /software/simsite/stratify.htm (1395 words)

	Chapter 7
		The usual goal in sampling is to produce a representative sample (i.e., a sample that is similar to the population on all characteristics, except that it includes fewer people because it is a sample rather than the complete population).
		Sampling error refers to the difference between the value of a sample statistic, such as the sample mean, and the true value of the population parameter, such as the population mean.
		Sampling experts recommend random sampling "without replacement" rather than random sampling "with replacement" because the former is a little more efficient in producing representative samples (i.e., it requires slightly fewer people and is therefore a little cheaper).
	www.southalabama.edu /coe/bset/johnson/dr_johnson/lectures/lec7.htm (2496 words)

	PA 765: Sampling
		Repeated systematic sample has the side benefit that the variability in the subsample means for a given variable is a measure of the variance of that estimate in the entire sample.
		Multi-stage or cluster sampling is where the researcher divides the population into strata, samples the strata, then stratifies the samples, and then resamples, repeating the process until the ultimate sampling units are selected at the last of the hierarchical levels.
		The researcher seeks to identify variables where the sample mean deviates from the population mean, and speculates (preferably on the basis of prior literature) on the impact of such bias on the dependent variables of interest.
	www2.chass.ncsu.edu /garson/pa765/sampling.htm (4871 words)

	stratification
		If, before drawing the sample, the school roll is divided by age and sex, and a separate sample is drawn per age and sex stratum, then if the sampling fraction of 1 in 20 is used in each stratum the sample would be a proportionate stratified sample.
		The sampling fraction to be applied in the white stratum would be 1 in 38; the sampling fraction to be applied in the non-white stratum would be 1 in 2.
		If the same sampling fraction is used in each stratum this is termed ‘proportionate stratified sample’; if the sample fraction is not the same in each stratum this is termed ‘disproportionate sampling’.
	www.dcs.napier.ac.uk /peas/textversions/textstratification.htm (1711 words)

	Stratified sampling - CGAFaq
		In Monte Carlo ray tracing, stratified sampling is a technique used to reduce the amount of noise in an image; it is one of many variance reduction techniques.
		Stratified sampling partitions the domain into multiple pieces, and takes a number of samples in each piece proportional to its size.
		At first, stratified sampling and importance sampling might appear to be contradictory techniques: stratified sampling tries to spread out samples evenly over the domain, whereas importance sampling concentrates samples into specific regions.
	cgafaq.info /wiki/Stratified_Sampling (1114 words)

	An integration of stratified sampling designs and Geographic Information Systems - An application in Educational ...
		However, sampling units within geographic regions may not be homogeneous and therefore, sample may not be representative, if the variation of spatial variables affecting the study variables were not considered in stratification.
		Therefore, sampling units drawn from strata based on administrative boundaries cannot be thought to be representative of wider areas and hence do not offer scope for the generalization or extrapolation of research results.
		Area was stratified using the spatial variables on the infrastructure facilities thus forming first stage strata and schools were stratified by using non-spatial variables on the facilities available in schools and these school strata were used as second stage strata in two-stage stratified sampling designs.
	www.gisdevelopment.net /education/papers/mi03147abs.htm (536 words)

	Smart Tags
		But with disproportionate stratified sampling, the weighted formula needs to be used because the strata sizes do not reflect their relative proportions in the population.
		In the one-step area sample approach, the researcher may believe the various geographic areas to be sufficiently identical to permit him or her to concentrate his or her attention on just one area and then generalize the results to the full population.
		That is, for the first step, the researcher could select a random sample of areas, and then for the second step, he or she could decide on a probability method to sample individuals within the chosen areas.
	www.insightexpress.com /ix/smartTag.asp?chapter=12 (1053 words)

	Probability Sampling
		Because simple random sampling is a fair way to select a sample, it is reasonable to generalize the results from the sample back to the population.
		Simple random sampling is not the most statistically efficient method of sampling and you may, just because of the luck of the draw, not get good representation of subgroups in a population.
		The problem with random sampling methods when we have to sample a population that's disbursed across a wide geographic region is that you will have to cover a lot of ground geographically in order to get to each of the units you sampled.
	www.socialresearchmethods.net /kb/sampprob.htm (2446 words)

	Chapter 7: Sampling In Marketing Research
		Sampling points are selected on the basis of numbers drawn at random that equate to the numbered columns and rows of the grid.
		It cannot assume that simply because the sample mean was 10.5 litres that this is necessarily a good estimate of the average purchases of all farmers in the population.
		Sampling bias arises when selection is consciously or unconsciously influenced by human choice, the sampling frame inadequately covers the target population or some sections of the population cannot be found or refuse to co-operate.
	www.fao.org /docrep/W3241E/w3241e08.htm (6225 words)

	Sampling (Site not responding. Last check: 2007-10-22)
		In a multistage random sample, a large area, such as a country, is first divided into smaller regions (such as states), and a random sample of these regions is collected.
		In the second stage, a random sample of smaller areas (such as counties) is taken from within each of the regions chosen in the first stage.
		Then, in the third stage, a random sample of even smaller areas (such as neighborhoods) is taken from within each of the areas chosen in the second stage.
	www.stat.yale.edu /Courses/1997-98/101/sample.htm (589 words)

	PlanetMath: stratified sampling
		In sampling surveys, it is sometimes a good idea to break up the population into subdivisions before any sampling were to take place.
		To insure that the sample taken preserves claim frequencies by gender, we would take a stratified sampling.
		This is version 2 of stratified sampling, born on 2005-05-19, modified 2005-05-19.
	planetmath.org /encyclopedia/Stratum.html (310 words)

	Stratified Sampling (Site not responding. Last check: 2007-10-22)
		Stratified sampling - Stratified sampling is a method of sampling from a population in statistics.
		Quota sampling - In quota sampling, the population is first segmented into mutually exclusive sub-groups, just as in stratified sampling.
		This often improves the accuracy of estimation efficient sampling equal numbers from strata varying widely in size may be used equate the statistical power of tests of differences between strata.
	ea58.motorists-mico.com /stratifiedsampling.html (1125 words)

	Chalmers_Technical Definition (Site not responding. Last check: 2007-10-22)
		For example, a country may be stratified into states, a state stratified into counties, a county stratified into cities and rural areas, etc. Suppose there is a county that consists of two cities and a rural area.
		First, stratifying the sample usually produces a smaller error in estimation than using a simple random sample of the same size.
		The total sample size is determined by the surveyor, based on the desired amount of error in estimation.
	www.tek-ritr.com /462/web_project/group_5/extras/documents/chalmers/Chalmers_Technical_Definition.htm (776 words)

	Sampling methods applied to fisheries science: a manual.
		The theory of stratified sampling deals with the properties of the sampling distribution of the estimators and with different types of allocation of the sample sizes to obtain the maximum precision.
		Sample size should be larger in strata that are larger, with greater variability and where sampling has lower cost.
		The optimum allocation of the sample to the strata in this situation is allocating sample size to the strata proportional to the size, and the standard error, and inversely proportional to the cost of sampling in each stratum.
	www.fao.org /docrep/009/a0198e/A0198E06.htm (1268 words)

	Stratified Sampling (Site not responding. Last check: 2007-10-22)
		In this random sampling technique, the whole population is first into mutually exclusive subgroups or strata and then units are selected randomly from each stratum.
		This is referred to as "proportionate stratified sampling".
		Disproportionate sampling is only undertaken if a particular strata is very important to the research project but occurs in too small a percentage to allow for meaningful analysis unless is representation is artificially boosted.
	www.ryerson.ca /~mjoppe/ResearchProcess/StratifiedSampling.htm (308 words)

	Stratified Sampling
		A stratified sample is generated by separating the population into a number of non-overlapping regions, called strata.
		Stratified sampling can increase the accuracy of population estimates where the selected strata have less variance than the population as a whole.
		for a stratified survey is given by the stratified sample average
	www.see.ed.ac.uk /~gaa/EYESManual/node3.html (184 words)

	Stemflow estimation in a redwood forest using model-based stratified random sampling (Site not responding. Last check: 2007-10-22)
		Description: Model-based stratified sampling is illustrated by a case study of stemflow volume in a redwood forest.
		The approach is actually a model-assisted sampling design in which auxiliary information (tree diameter) is utilized in the design of stratum boundaries to optimize the efficiency of a regression or ratio estimator.
		The advantage of the ratio estimator over standard stratified sampling formulas is greatest for species in which stemflow is strongly dependent on diameter.
	www.treesearch.fs.fed.us /pubs/viewpub.jsp?index=7810 (263 words)

	Natural Resource Biometrics - Stratified Sampling (Site not responding. Last check: 2007-10-22)
		If this population were sampled for density without considering the differences in the regions of the population the estimate of variance will be higher.
		The sample means are plotted as solid lines, with the overall mean thicker than the two strata means.
		The sample standard deviations (s) are plotted as dashed line with the overall line thicker that the strata lines.
	www.snr.missouri.edu /NR211/topics/stratify.html (420 words)

	Stratified sampling (Site not responding. Last check: 2007-10-22)
		Stratified sampling is used if sampled area (or volume) is heterogeneous (Pielou, p.107).
		In stratified sampling program, the area (volume) is subdivided into 2 or more portions which are sampled separately.
		Example: pine sawflies prefer to spin their cocoons close to the tree; thus, the area adjacent to trees (within 1 m radius) can be sampled separately from the rest of the area.
	www.ento.vt.edu /~sharov/PopEcol/lec2/stratif.html (166 words)

	Powder Blends and Finished Dosage Units - Stratified In-Process Dosage Unit Sampling and Assessment
		Stratified sampling is the process of sampling dosage units at predefined intervals and collecting representative samples from specifically targeted locations in the compression/filling operation that have the greatest potential to yield extreme highs and lows in test results.
		Correlate the stratified sample data with the finished dosage unit data and assess uniformity of content.
		Sampling problems may also be negated by use of alternate state-of-the-art methods of in situ real-time sampling and analysis.
	www.fda.gov /cder/guidance/5831dft.htm (4848 words)

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