Formula for standard error (SEM) is standard deviation divided by the square root of the sample size, or s/sqrt(n). SEM = 100/sqrt25 = 100/5 = 20.
the sample standard deviation
Yes.
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)]
Not a lot. After all, the sample sd is an estimate for the population sd.
The standard deviation of the population. the standard deviation of the population.
Formula for standard error (SEM) is standard deviation divided by the square root of the sample size, or s/sqrt(n). SEM = 100/sqrt25 = 100/5 = 20.
No.
Yes
The standard deviation if the data is a sample from a population is 7.7115; if it is the population the standard deviation is 7.0396.
the sample standard deviation
Yes.
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)]
Not a lot. After all, the sample sd is an estimate for the population sd.
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.
The true / real standard deviation ("the mean deviation from the mean so to say") which is present in the population (everyone / everything you want to describe when you draw conclusions)
Standard deviation is 0.