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The mean, by itself, does not provide sufficient information to make any assessment of the sample variance.
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∙ 12y ago
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How do you calculate distribution of sample means?
The sample mean is distributed with the same mean as the popualtion mean. If the popolation variance is s2 then the sample mean has a variance is s2/n. As n increases, the distribution of the sample mean gets closer to a Gaussian - ie Normal - distribution. This is the basis of the Central Limit Theorem which is important for hypothesis testing.
Can the variance of a sample be larger than the sample mean?
Yes, Mean is given by, E(X) sum of samples / no. of samples. Variance is Var.(X) = E(X^2) - [E(X)]^2. It is the 1st term which makes the variation of variance independent of mean. In other words, Variance gives a measure of how far the samples are spread out.
What is not dependent on the size of a sample?
In general the mean of a truly random sample is not dependent on the size of a sample. By inference, then, so is the variance and the standard deviation.
What is the sample variance of 5781010 and 14?
The variance is: 1.6709957376e+13
How do you prove that the sample variance is equal to the population variance?
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.
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.
How do you calculate distribution of sample means?
The sample mean is distributed with the same mean as the popualtion mean. If the popolation variance is s2 then the sample mean has a variance is s2/n. As n increases, the distribution of the sample mean gets closer to a Gaussian - ie Normal - distribution. This is the basis of the Central Limit Theorem which is important for hypothesis testing.
When using the distribution of sample mean to estimate the population mean what is the benefit of using larger sample sizes?
The variance decreases with a larger sample so that the sample mean is likely to be closer to the population mean.
Can the variance of a sample be larger than the sample mean?
Yes, Mean is given by, E(X) sum of samples / no. of samples. Variance is Var.(X) = E(X^2) - [E(X)]^2. It is the 1st term which makes the variation of variance independent of mean. In other words, Variance gives a measure of how far the samples are spread out.
What is mean of any calculated number from a sample from the population is called statics such as the mean or the variance?
i mean conclucion
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.
How much error between sample mean and population mean?
The answer depends on the underlying variance (standard deviation) in the population, the size of the sample and the procedure used to select the sample.
What is not dependent on the size of a sample?
In general the mean of a truly random sample is not dependent on the size of a sample. By inference, then, so is the variance and the standard deviation.
Is sample variance unbiased estimator of population variance?
No, it is biased.
What is the sample variance of 5781010 and 14?
The variance is: 1.6709957376e+13
How do you prove that the sample variance is equal to the population variance?
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.
Can the variance of a sample be negaTIve?
No.
