Both are measures of the spread of the data around a mean or average. In fact the standard deviation == sqrt(variance). The standard deviation (SD) is defined to be the square root of the sample variance (V).
EX: Some value X = M +/- 1 SD indicates that there is roughly a 2/3 probability that the value will fall randomly within the interval from minus one SD up to plus one SD around the mean M.
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.
It means that there are is no variation from the mean. In other words, all values in your sample are identical.
A single observation cannot have a sample standard deviation.
The standard deviation of the population. the standard deviation of the population.
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.
It simply means that you have a sample with a smaller variation than the population itself. In the case of random sample, it is possible.
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)]
Yes, but only in the case where all numbers in your sample are the same. If you attempt to use a zero standard deviation in most statistical analyses, you will get an error message. Your sample has shown no variation so no inferences can be made to the general population.
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
The answer is False