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Not to take sides is to remain what?
unbiased.
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 is the difference between sample and sample size?
a sample is a sample sized piece given... a sample size is the amount given in one sample
What would be a better tool for measuring spread and center in statistics?
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.
What is objectivity in statistics?
the use of random sampling that results in an unbiased conclusion.
What is the definition for unbiased sample?
A sample is Unbiased if everyone in the sample have an equal chance of being selected
Is a sample UNBIASED?
Only if you make it unbiased. Samples can be weird. If you make it unbiased, then yes.
What is the proof that the sample variance is an unbiased estimator?
The proof that the sample variance is an unbiased estimator involves showing that, on average, the sample variance accurately estimates the true variance of the population from which the sample was drawn. This is achieved by demonstrating that the expected value of the sample variance equals the population variance, making it an unbiased estimator.
Why is the sample mean an unbiased estimator of the population mean?
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.
Show that in simple random sampling the sample variance is an unbiased estimator of population variance?
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.
Is sample variance unbiased estimator of population variance?
No, it is biased.
How are biased and unbiased sample similar?
They are samples from a population, but otherwise they are not similar.
What is the difference between a biased and unbiased sample?
Biased- (Not random) Unbiased-(Random) Example: (ubbiased) Woman takes random people to take a survey.
What would an unbiased firm gather?
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.
Is there a proof that demonstrates the unbiasedness of the sample variance?
Yes, there is a mathematical proof that demonstrates the unbiasedness of the sample variance. This proof shows that the expected value of the sample variance is equal to the population variance, making it an unbiased estimator.
What does it mean to say that the sample variance provides an unbiased estimate of the population variance?
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.
What is the the relationship between population and sample parameter and statistic?
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.
