The answer will depend on the population mean of what variable? Height?, length or is it simply weight. If it is weight, the estimated (not estimd) population mean is 3.01 units: the same as the sample mean. The standard deviation (not diviation) is irrelevant.
The answer will depend on the population mean of what variable? Height?, length or is it simply weight. If it is weight, the estimated (not estimd) population mean is 3.01 units: the same as the sample mean. The standard deviation (not diviation) is irrelevant.
The answer will depend on the population mean of what variable? Height?, length or is it simply weight. If it is weight, the estimated (not estimd) population mean is 3.01 units: the same as the sample mean. The standard deviation (not diviation) is irrelevant.
The answer will depend on the population mean of what variable? Height?, length or is it simply weight. If it is weight, the estimated (not estimd) population mean is 3.01 units: the same as the sample mean. The standard deviation (not diviation) is irrelevant.
The answer will depend on the population mean of what variable? Height?, length or is it simply weight. If it is weight, the estimated (not estimd) population mean is 3.01 units: the same as the sample mean. The standard deviation (not diviation) is irrelevant.
The sample standard error.
If the population standard deviation is sigma, then the estimate for the sample standard error for a sample of size n, is s = sigma*sqrt[n/(n-1)]
The standard deviation of the population. the standard deviation of the population.
Not a lot. After all, the sample sd is an estimate for the population sd.
Standard error of the sample mean is calculated dividing the the sample estimate of population standard deviation ("sample standard deviation") by the square root of sample size.
Yes
n = sample sizen1 = sample 1 sizen2 = sample 2 size= sample meanμ0 = hypothesized population meanμ1 = population 1 meanμ2 = population 2 meanσ = population standard deviationσ2 = population variance
Sure it can. But in the survey business, the trick is to select your sample carefully so that they'll be equal, i.e. a sample that is accurately representative of the population.
the sample standard deviation
If the samples are drawn frm a normal population, when the population standard deviation is unknown and estimated by the sample standard deviation, the sampling distribution of the sample means follow a t-distribution.
What is the sample mean?
the standard deviation of the sample decreases.