what is the difference between sampling error and non sampling error?
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Sampling Error
“Sampling error is the error that arises in a data collection process as a result of taking a sample from a population rather than using the whole population.
Sampling error is one of two reasons for the difference between an estimate of a population parameter and the true, but unknown, value of the population parameter. The other reason is non-sampling error. Even if a sampling process has no non-sampling errors then estimates from different random samples (of the same size) will vary from sample to sample, and each estimate is likely to be different from the true value of the population parameter.
The sampling error for a given sample is unknown but when the sampling is random, for some estimates (for example, sample mean, sample proportion) theoretical methods may be used to measure the extent of the variation caused by sampling error.”
Non-sampling error:
“Non-sampling error is the error that arises in a data collection process as a result of factors other than taking a sample.
Non-sampling errors have the potential to cause bias in polls, surveys or samples.
There are many different types of non-sampling errors and the names used to describe them are not consistent. Examples of non-sampling errors are generally more useful than using names to describe them.
“Sampling error is the error that arises in a data collection process as a result of taking a sample from a population rather than using the whole population.
Sampling error is one of two reasons for the difference between an estimate of a population parameter and the true, but unknown, value of the population parameter. The other reason is non-sampling error. Even if a sampling process has no non-sampling errors then estimates from different random samples (of the same size) will vary from sample to sample, and each estimate is likely to be different from the true value of the population parameter.
The sampling error for a given sample is unknown but when the sampling is random, for some estimates (for example, sample mean, sample proportion) theoretical methods may be used to measure the extent of the variation caused by sampling error.”
Non-sampling error:
“Non-sampling error is the error that arises in a data collection process as a result of factors other than taking a sample.
Non-sampling errors have the potential to cause bias in polls, surveys or samples.
There are many different types of non-sampling errors and the names used to describe them are not consistent. Examples of non-sampling errors are generally more useful than using names to describe them.
Answered by
70
"Difference between sampling error and non-sampling error is given below.
Sampling error:
- The error which occurs due to a problem in the sample it is called sampling error.
- It is caused when a difference occurs in sample mean and actual mean.
- It is always of random type.
Non-Sampling error:
- The error which is caused by human which includes implementation of the wrong method is called non-sampling error.
- It is caused due to lack of concentration while analyzing.
- It is of both types namely random or non-random."
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