Study guides

☆☆

Q: When would random sampling not be the best approach to sample selection?

Write your answer...

Submit

Still have questions?

Continue Learning about Statistics

Statistical sampling is an objective approach using probability to make an inference about the population. The method will determine the sample size and the selection criteria of the sample. The reliability or confidence level of this type of sampling relates to the number of times per 100 the sample will represent the larger population. Non-statistical sampling relies on judgment to determine the sampling method,the sample size,and the selection items in the sample.

simple random sample is to select the sample in random method but systematic random sample is to select the sample in particular sequence (ie 1st 11th 21st 31st etc.)â€¢ Simple random sample requires that each individual is separately selected but systematic random sample does not selected separately.â€¢ In simple random sampling, for each k, each sample of size k has equal probability of being selected as a sample but it is not so in systematic random sampling.

In a stratified sample, the sampling proportion is the same for each stratum. In a random sample it should be but, due to randomness, need not be.

I believe you meant to ask: What distinguishes a random sample from a non random sample? A random sample means the selection or sampling from the population is by chance. Looking at the data, one might not be able to tell if the sample is random or selective. Consider a marketing survey which is included everytime you buy an item online. Random or non-random? It is a survey of recent customers, and probably a pretty good one. But it is not a random selection of all customers who have made purchases with clients.

It is a biased estimator. S.R.S leads to a biased sample variance but i.i.d random sampling leads to a unbiased sample variance.

Related questions

random sampling

stratified sampling, in which the population is divided into classes, and random samples are taken from each class;cluster sampling, in which a unit of the sample is a group such as a household; andsystematic sampling, which refers to samples chosen by any system other than random selection.

Statistical sampling is an objective approach using probability to make an inference about the population. The method will determine the sample size and the selection criteria of the sample. The reliability or confidence level of this type of sampling relates to the number of times per 100 the sample will represent the larger population. Non-statistical sampling relies on judgment to determine the sampling method,the sample size,and the selection items in the sample.

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

simple random sample is to select the sample in random method but systematic random sample is to select the sample in particular sequence (ie 1st 11th 21st 31st etc.)â€¢ Simple random sample requires that each individual is separately selected but systematic random sample does not selected separately.â€¢ In simple random sampling, for each k, each sample of size k has equal probability of being selected as a sample but it is not so in systematic random sampling.

In a stratified sample, the sampling proportion is the same for each stratum. In a random sample it should be but, due to randomness, need not be.

Random sampling can be defined as the selection of a random sample; each element of the population had an equal chance of been selected. Random sampling is used in psychology, statistics, math, sociology, movement and research.

A questionnaire has little to do with sampling technique. Sampling technique is to do with who gets the questionnaire and that can be any sampling technique: the questionnaire can be sent to everyone (census), to a random sample, stratified random samples, to random samples in clusters, by quota or convenience. Or a pile of questionnaires can be left for respondents to pick up - self-selection.

I believe you meant to ask: What distinguishes a random sample from a non random sample? A random sample means the selection or sampling from the population is by chance. Looking at the data, one might not be able to tell if the sample is random or selective. Consider a marketing survey which is included everytime you buy an item online. Random or non-random? It is a survey of recent customers, and probably a pretty good one. But it is not a random selection of all customers who have made purchases with clients.

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.

stratified random sampling is a sample(strata) that a same and hemogenieous in group and that a different and heterogenious in group

It is a biased estimator. S.R.S leads to a biased sample variance but i.i.d random sampling leads to a unbiased sample variance.

People also asked