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Q: Is mean an unbiased estimator of a population?
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Which of the following best describes the condition necessary to justify using a pooled estimator of the population variance?

1- Assuming this represents a random sample from the population, the sample mean is an unbiased estimator of the population mean. 2-Because they are robust, t procedures are justified in this case. 3- We would use z procedures here, since we are interested in the population mean.


Why median is not a consistent estimator?

Because it is easily influenced by extreme values (i.e. it is not unbiased).


What is an unbiased estimator?

An unbiased estimator is a person who gives a price for a service or goods and that person has no ulterior motives that would influence the price either way. A person who is biased might reflect the estimated price to show favor to one person more than another. For example: If my uncle was to bid on a job and I was the estimator for the person who wanted the work done, then I would have a bias in that I would reflect the price so that my uncle would get the job. This is unethical and illegal. An unbiased person has no preference as to who would get the job and would do the estimate honestly. An unbiased estimator has a very specific meaning in statistics and a good statistician needs to answer this meaning of the term.


What is the uses of ratio estimator?

what is the use and application of ratio estimator?


How large would your sample have to be for appropriate estimation of the whole population?

First you have chose an estimator for what you want to know about the population. In general the level of variability in the result that any estimator provides will depend on the variability in the population. Therefore, the greater the variability in the population the larger your sample size must be. You will also need to decide how much precision is required in your estimate. The more precision you require the greater your sample size will have to be.