Respuesta :
Statistical uncertainty in estimates associated with the fact that surveys do not interview every individual in the population of interest is called Sampling Error , Option D is the correct answer.
What is Sampling Error ?
Sampling error is the difference between the estimated value and the true value if the whole population was enumerated while doing the sampling.
By following the sampling principles one can keep the sampling error to the minimum.
The knowledge of the sampling error will help in evaluating the sampling process and defining gits efficiency.
The factors that affect Sampling Error are
- Sample Size: When the sample size is large , the Sampling error decreases , They do not have a direct proportion.
- Sample Design : These define how the sample will be taken , cluster , random , stratified , Different methods have different extent of sampling error , The design should be selected according to the population and resources constraints.
- Population Variability : The variability in the population increases the sampling error as the sampling is then cannot be uniform and cannot represent the entire population , By increasing sample size , the population variability can be minimized and so the sampling error.
Statistical uncertainty in estimates associated with the fact that surveys do not interview every individual in the population of interest is called sampling Error.
Therefore , Option D is the correct answer.
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