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Q: Is the sample mean a consistent estimator of population mean?
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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.


What does n-1 indicate in a calculation for variance?

The n-1 indicates that the calculation is being expanded from a sample of a population to the entire population. Bessel's correction(the use of n − 1 instead of n in the formula) is where n is the number of observations in a sample: it corrects the bias in the estimation of the population variance, and some (but not all) of the bias in the estimation of the population standard deviation. That is, when estimating the population variance and standard deviation from a sample when the population mean is unknown, the sample variance is a biased estimator of the population variance, and systematically underestimates it.


Difference between calculating the sample mean and the population mean?

The same basic formula is used to calculate the sample or population mean. The sample mean is x bar and the population mean is mu. Add all the values in the sample or population and divide by the number of data values.


Why wont a sample statistics change from sample to sample?

The sample mean may differ from the population mean, especially for small samples.


What is the estimated population mean with a sample of 36 and a standard deviation of 0.03?

What is the sample mean?