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Circular systematic sampling is a random sampling method. An example is random sampling of households. Assume that a random number generator provides the number 49 as a starting point. Starting with the household that is 49 on the target list, every nth household on the list would be sampled until the desired sample size is reached

Q: What is circular systematic sampling?

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Simple Random Sample Stratified Random Sampling Cluster Sampling Systematic Sampling Convenience Sampling

Systematic sampling

You are correct; convenience sampling is not random sampling.

Clustered sampling.Clustered sampling.Clustered sampling.Clustered 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.

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You can't conduct startified sampling if there are no difinative groups, thus systematic sampling is more efficient if your data has no groups.

They include: Simple random sampling, Systematic sampling, Stratified sampling, Quota sampling, and Cluster sampling.

Random sampling is picking a subject at random. Systematic sampling is using a pattern to pick subjects, I.e. picking every third person.

Simple Random Sample Stratified Random Sampling Cluster Sampling Systematic Sampling Convenience Sampling

Compare the efficiency of simple random sampling with systematic random sampling for estimating the population mean and give your comments.

efficiency

Disadvantages of systematic sampling: © The process of selection can interact with a hidden periodic trait within the population. If the sampling technique coincides with the periodicity of the trait, the sampling technique will no longer be random and representativeness of the sample is compromised.

Answer is Quota sampling. Its one of the method of non-probability sampling.

Sampling error leads to random error. Sampling bias leads to systematic error.

random sampling ,systematic sampling , self-selected , and there is one more i don't know

Nothing! there the same

Stratified random sampling.