unbiased.
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.
a sample is a sample sized piece given... a sample size is the amount given in one sample
The answer will depend on what the comparison is to be made with and also on how "better" is being judged. The arithmetic average is the best linear unbiased estimate as well as the maximum likelihood estimate of the centre. The best estimate for the spread depends on whether the data comprise the population or a sample from the population.
the use of random sampling that results in an unbiased conclusion.
A sample is Unbiased if everyone in the sample have an equal chance of being selected
Only if you make it unbiased. Samples can be weird. If you make it unbiased, then yes.
The sample mean is an unbiased estimator of the population mean because the average of all the possible sample means of size n is equal to the population mean.
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.
No, it is biased.
They are samples from a population, but otherwise they are not similar.
Biased- (Not random) Unbiased-(Random) Example: (ubbiased) Woman takes random people to take a survey.
Enough data to be reprsentative Fair questions and appropriate answer choices or measure of answer An unbiased sample Conclusions that reflect the study accurately and not beyond the limits of the study.
It means you can take a measure of the variance of the sample and expect that result to be consistent for the entire population, and the sample is a valid representation for/of the population and does not influence that measure of the population.
The relations depend on what measures. The sample mean is an unbiased estimate for the population mean, with maximum likelihood. The sample maximum is a lower bound for the population maximum.
The best estimator of the population mean is the sample mean. It is unbiased and efficient, making it a reliable estimator when looking to estimate the population mean from a sample.
The standard deviation. There are many, and it's easy to construct one. The mean of a sample from a normal population is an unbiased estimator of the population mean. Let me call the sample mean xbar. If the sample size is n then n * xbar / ( n + 1 ) is a biased estimator of the mean with the property that its bias becomes smaller as the sample size rises.