No, the standard deviation is a measure of the entire population.
The sample standard deviation is an unbiased estimator of the population. It is different in notation and is written as 's' as opposed to the greek letter sigma.
Mathematically the difference is a factor of
n/(n-1)
in the variance of the sample. As you can see the value is greater than 1 so it will increase the value you get for your sample mean.
Essentially, this covers for the fact that you are unlikely to obtain the full population variation when you sample.
The standard deviation is the square root of the variance.
Standard error of the mean (SEM) and standard deviation of the mean is the same thing. However, standard deviation is not the same as the SEM. To obtain SEM from the standard deviation, divide the standard deviation by the square root of the sample size.
A single observation cannot have a sample standard deviation.
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)]
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.
The standard deviation is the square root of the variance.
Standard error of the mean (SEM) and standard deviation of the mean is the same thing. However, standard deviation is not the same as the SEM. To obtain SEM from the standard deviation, divide the standard deviation by the square root of the sample size.
A single observation cannot have a sample standard deviation.
The standard deviation of the population. the standard deviation of the population.
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)]
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.
the sample standard deviation
Standard deviation in statistics refers to how much deviation there is from the average or mean value. Sample deviation refers to the data that was collected from a smaller pool than the population.
Suppose the mean of a sample is 1.72 metres, and the standard deviation of the sample is 3.44 metres. (Notice that the sample mean and the standard deviation will always have the same units.) Then the coefficient of variation will be 1.72 metres / 3.44 metres = 0.5. The units in the mean and standard deviation 'cancel out'-always.
Not a lot. After all, the sample sd is an estimate for the population sd.
Here's how you do it in Excel: use the function =STDEV(<range with data>). That function calculates standard deviation for a sample.