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Which sampling is obtained by dividing the population into groups and selecting all individuals from within a random sample of the groups?
It is called one-stage cluster sampling. If random samples are taken within the selected clusters then it is two-stage cluster sampling.
What is 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 non-sampling errors. But disadvantage is that it limits the amount of stratification that can be employed. IPS(interpenetrating sampling) provides a quick, simple, and effective way of estimating the variance of an estimator even in a complex survey. In fact, IPS is the foundation of modern resampling methods like Jackknife, bootstrap, and replication methods. In IPS, three basic principles of experimental designs, namely, randomization, replication, and local control, are used. IPS is used extensively not only in agriculture, but also in social sciences, demography, epidemiology, public health, and many other fields.
What are four kinds of sampling techniques?
Four sampling techniques are:1) Simple Random SamplingThis is the ideal choice as it is a 'perfect' random method. Using this method, individuals are randomly selected from a list of the population and every single individual has an equal chance of selection.This method is ideal, but if it cannot be adopted, one of the following alternatives may be chosen if any shortfall in accuracy.2) Systematic SamplingSystematic sampling is a frequently used variant of simple random sampling. When performing systematic sampling, every kth element from the list is selected (this is referred to as the sample interval) from a randomly selected starting point. For example, if we have a listed population of 6000 members and wish to draw a sample of 2000, we would select every 30th (6000 divided by 200) person from the list. In practice, we would randomly select a number between 1 and 30 to act as our starting point.The one potential problem with this method of sampling concerns the arrangement of elements in the list.? If the list is arranged in any kind of order e.g. if every 30th house is smaller than the others from which the sample is being recruited, there is a possibility that the sample produced could be seriously biased.3) Stratified SamplingStratified sampling is a variant on simple random and systematic methods and is used when there are a number of distinct subgroups, within each of which it is required that there is full representation. A stratified sample is constructed by classifying the population in sub-populations (or strata), base on some well-known characteristics of the population, such as age, gender or socio-economic status. The selection of elements is then made separately from within each strata, usually by random or systematic sampling methods.Stratified sampling methods also come in two types - proportionate and disproportionate.In proportionate sampling, the strata sample sizes are made proportional to the strata population sizes.For example if the first strata is made up of males, then as there are around 50% of males in the UK population, the male strata will need to represent around 50% of the total sample. In disproportionate methods, the strata are not sampled according to the population sizes, but higher proportions are selected from some groups and not others. This technique is typically used in a number of distinct situations:The costs of collecting data may differ from subgroup to subgroup.We might require more cases in some groups if estimations of populations values are likely to be harder to make i.e. the larger the sample size (up to certain limits), the more accurate any estimations are likely to be.We expect different response rates from different groups of people. Therefore, the less co-operative groups might be 'over-sampled' to compensate.4) Cluster or Multi-stage SamplingCluster sampling is a frequently-used, and usually more practical, random sampling method. It is particularly useful in situations for which no list of the elements within a population is available and therefore cannot be selected directly. As this form of sampling is conducted by randomly selecting subgroups of the population, possibly in several stages, it should produce results equivalent to a simple random sample.The sample is generally done by first sampling at the higher level(s) e.g. randomly sampled countries, then sampling from subsequent levels in turn e.g. within the selected countries sample counties, then within these postcodes, the within these households, until the final stage is reached, at which point the sampling is done in a simple random manner e.g. sampling people within the selected households. The 'levels' in question are defined by subgroups into which it is appropriate to subdivide your population.Cluster samples are generally used if:- No list of the population exists.- Well-defined clusters, which will often be geographic areas exist.- A reasonable estimate of the number of elements in each level of clustering can be made.- Often the total sample size must be fairly large to enable cluster sampling to be used effectively.Non-probability Sampling MethodsNon-probability sampling procedures are much less desirable, as they will almost certainly contain sampling biases. Unfortunately, in some circumstances such methods are unavoidable. In a Market Research context, the most frequently-adopted form of non-probability sampling is known as quota sampling.? In some ways this is similar to cluster sampling in that it requires the definition of key subgroups. The main difference lies in the fact that quotas (i.e. the amount of people to be surveyed) within subgroups are set beforehand (e.g. 25% 16-24 yr olds, 30% 25-34 yr olds, 20% 35-55 yr olds, and 25% 56+ yr olds) usually proportions are set to match known population distributions. Interviewers then select respondents according to these criteria rather than at random. The subjective nature of this selection means that only about a proportion of the population has a chance of being selected in a typical quota sampling strategy.If you are forced into using a non-random method, you must be extremely careful when drawing conclusions. You should always be honest about the sampling technique used and that a non-random approach will probably mean that biases are present within the data. In order to convert the sample to be representative of the true population, you may want to use weighting techniques.The importance of sampling should not be underestimated, as it determines to whom the results of your research will be applicable. It is important, therefore to give full consideration to the sampling strategy to be used and to select the most appropriate. Your most important consideration should be whether you could adopt a simple random sample.? If not, could one of the other random methods be used? Only when you have no choice should a non-random method be used.All to often, researchers succumb to the temptation of generalising their results to a much broader range of people than those from whom the data was originally gathered. This is poor practice and you should always aim to adopt an appropriate sampling technique. The key is not to guess, but take some advice.
At what stage should you begin to think about the kinds of data analysis you need to conduct?
Answer: As early as possible. Most of the time, the observational or experimental studies consider what type of data analyses may be needed in the conceptual and planning stages. The conceptual stage is often called the brainstorming stage, where there is an open flow of ideas and opinions. The planning stage narrows the focus and culls out the best approaches.
What is the difference between a mistake and an error in statistics for research?
The Difference between the real value and the expected value creates Error of Origin. Whereas wrong statistical method used in the research or we calculated in a wrong way this is called mistake in stats.Errors are not willingly done but mistakes are done knowinglyError occurs at the stage of Collecting data, Analyzing it or at the time of Interpretation. Whereas Mistakes can be done at any stage of Research.Predicting Error is easy but it is difficult while making mistake in research.One cannot stop Errors but we can stop making mistakes in research.Posted by Elana Bhandari,Jodhpur.
What is the difference between two phase and double sampling?
what is the difference betwee two stage and two phase sampling
What is multi-phase research?
Is the similar to mult-stage sampling but only different is that insteady of conducting in lastly stage but mult-phase conducted in every phase and this type of sampling is applicable in a big organization which is enough fund.
What is the difference between multiphase sampling and multistage sampling?
in multi-stage sampling the population is divided into a nonumber of units & in multi-phase sapling when certain items of information are collected from all the units in a sample and other itemsof usually more detailed information are collected from the subsample of the units composing the original sample.
What is the difference between double sampling and multiphase sampling?
DOUBLE SAMPLINGDefinition:A standard form of sample design for industrial inspection purposes. In accordance with the characteristics of a particular plan, two samples are drawn, n1 and n2, and the first sample inspected. The batch can then be accepted or rejected upon the results of this inspection or the second sample be inspected and the decision made upon the combined result.Context:The term has also been used somewhat loosely for what is called multi-phase sampling and the two-stage version of multi-stage sampling. There is a further usage whereby a first sample provides a preliminary estimate of design parameters which govern the size of the second sample to achieve a desired overall result.MULTI-PHASE SAMPLINGDefinition:It is sometimes convenient and economical to collect certain items of information from the whole of the units of a sample and other items of usually more detailed information from a sub-sample of the units constituting the original sample. This may be termed two-phase sampling, e.g. if the collection of information concerning variate, y, is relatively expensive, and there exists some other variate, x, correlated with it, which is relatively cheap to investigate, it may be profitable to carry out sampling in two phases.At the first phase, x is investigated, and the information thus obtained is used either (a) to stratify the population at the second phase, when y is investigated, or (b) as supplementary information at the second phase, a ratio or regression estimate being used.Two-phase sampling is sometimes called "double sampling".Context:Further phases may be added if desired. It may be noted, however, that multiphase sampling does not necessarily imply the use of any relationships between variates x and y. The expression is not to be confused with multi-stage sampling.
What is the analogy for phase stage?
Phase : stage ::
What is the difference between infective stage and diagnostic stage?
Infective stage is the life cycle stage where parasite able to initiate an infection in a definitive or intermediate host. Diagnostic stage is the life cycle stage leaving the definitive host, it is the stage that links the parasitic way of life with either the free-living phase of the life cycle or the phase of development that occurs in an intermediate host.
Example of panel sampling?
A good example to panel sampling will be sampling the performance of a group of companies in a specified region. This way they the samples can be revisited at a later stage thus panel sampling.
Which sampling is obtained by dividing the population into groups and selecting all individuals from within a random sample of the groups?
It is called one-stage cluster sampling. If random samples are taken within the selected clusters then it is two-stage cluster sampling.
What are the differences between stage direction and dialog notations?
stage direction is someone directing a play and dialogue is someone in the play
What is the procedure of convenience sampling?
Convenience sampling is also know as grab sampling. There is no procedure for the sampling itself because the emphasis at this stage is usually on improving other aspects of the research such as exposing flaws in a survey form or training personnel. In grab sampling you simply take any sample element that you can find although you might favour those that would exercise parts of your system that might seem weak. For instance, if your survey instrument asks for ages and some people were reluctant to provide them, then how would this be resolved once the grab sampling phase had been completed and actual sampling had started?
Stage two of the ISSA drawing-in phase is?
Stage two of the ISSA drawing in phase is data collection.
What are the differences between the Mamma Mia film and stage show?
2 girls 1 cup
