In general, you cannot.
If the distribution can be assumed to be Gaussian [Normal] then you could use z-scores.
Information is not sufficient to find mean deviation and standard deviation.
we calculate standard deviation to find the avg of the difference of all values from mean.,
No, you have it backwards, the standard deviation is the square root of the variance, so the variance is the standard deviation squared. Usually you find the variance first, as it is the average sum of squares of the distribution, and then find the standard deviation by squaring it.
Variance is 362 or 1296.
The variance is the square of the standard deviation.This question is equivalent tocan s = s^2The answer is yes, but only in two cases.If the standard deviation is 1 exactly, then so is the variance.If the standard deviation is 0 exactly, then so is the variance.If the standard deviation is anything else, then it is not equal to the variance.You are not likely to find these special cases in practical problems, so from a practical sense, you should think that they are generally not equal.
The range is 9 and 3.01 is the standard deviation.
Information is not sufficient to find mean deviation and standard deviation.
we calculate standard deviation to find the avg of the difference of all values from mean.,
No, you have it backwards, the standard deviation is the square root of the variance, so the variance is the standard deviation squared. Usually you find the variance first, as it is the average sum of squares of the distribution, and then find the standard deviation by squaring it.
You're an idiot. It's standard deviation. Google that for your answer.
You cannot because the median of a distribution is not related to its standard deviation.
A standard deviation calculator allows the user to find the mean spread away from the mean in a statistical environment. Most users needing to find the standard deviation are in the statistics field. Usually, the data set will be given and must be typed into the calculator. The standard deviation calculator will then give the standard deviation of the data. In order to find the variance of the data, simply square the answer.
to calculate the standard deviation you must put each number in order from the least to the gr east then you must find your mean after you find your mean you must subtract your mean from each of the data set numbers once you finishsubtracting the data set numbers you add them up and divide by the amount of numbers there are and you have found the 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)]
Look at the Wikipedia article on "Standard deviation" - it includes an example right at the beginning.
Standard deviation calculation is somewhat difficult.Please refer to the site below for more info
Standard deviations are measures of data distributions. Therefore, a single number cannot have meaningful standard deviation.