Want this question answered?
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.
No, it is biased.
You cannot prove it because it is not true.The expected value of the sample variance is the population variance but that is not the same as the two measures being the same.
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.
(Population) variance = 6.4664
yes, it can be smaller, equal or larger to the true value of the population varience.
1
the numerator of the F-ratio
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.
the small greek letter sigma squared.
The lognormal distribution, probably.
You can calculate standard deviation by addin the numbers of data that are together and dividing that number by the amount pieces of data.THAT IS TOTALLY INCORRECT.What was answered above was the calculation for getting an (mean) average.If you take five numbers for example 1, 2, 3, 4, 5 then the (mean) average is 3.But the standard deviation between them is 1.58814 and the variance is 2.5Also the population std. deviation will be 1.41421 and the population variance will be 2.see standard-deviation.appspot.com/