how to calculate variance of standard deviation is known?
142462
['Calculate the mean.', 'Subtract the mean from each observation.', 'Square each of the resulting observations.', 'Add these squared results together.', 'Divide this total by the number of observations (variance, S2).']
257852
To calculate the variance, you first subtract the mean from each number and then square the results to find the squared differences. You then find the average of those squared differences. The result is the variance.
273084
To figure out the variance, divide the sum, 82.5, by N-1, which is the sample size (in this case 10) minus 1. The result is a variance of 82.5/9 = 9.17. Standard deviation is the square root of the variance so that the standard deviation would be about 3.03.
1009774
If you square and average the difference between each number and the mean, the result is 82.5. To figure out the variance, subtract 82.5 from the mean, which is 5.5 and then divide by N, which is the value of numbers, (in this case 10) minus 1. The result is a variance of about 9.17.
659495
Standard deviation is calculated by first subtracting the mean from each value, and then squaring, adding, and averaging the differences to produce the variance.
97336
['Find the mean of all the x-values.', 'Find the standard deviation of all the x-values (call it sx) and the standard deviation of all the y-values (call it sy). ... ', 'For each of the n pairs (x, y) in the data set, take.', 'Add up the n results from Step 3.', 'Divide the sum by sx ∗ sy.']
471572
Since this is a binomial, then you can use the formula σ2=npq. f. Once you have the variance, you just take the square root of the variance to find the standard deviation.
317731
['The standard deviation formula may look confusing, but it will make sense after we break it down. ... ', 'Step 1: Find the mean.', 'Step 2: For each data point, find the square of its distance to the mean.', 'Step 3: Sum the values from Step 2.', 'Step 4: Divide by the number of data points.', 'Step 5: Take the square root.']
211525
['Calculate the mean (simple average of the numbers).', 'For each number: subtract the mean. Square the result.', 'Add up all of the squared results.', 'Divide this sum by one less than the number of data points (N - 1). ... ', 'Take the square root of this value to obtain the sample standard deviation.']
1021874
Sum up the squared deviations (the distances from each number to the mean) and take the mean of that number. This is the variance, or a rough measure of how spread out they are. To find the standard deviation you take the square root of the variance. Voila!
1150077
To calculate the standard deviation, we first calculate the variance. We use the expected value we calculated earlier: E[R] = -$0.053. So SD[R] = / . 997 = 0.999.
495703
Calculate the mean. Subtract the mean from each observation. ... Divide this total by the number of observations (variance, S2). Use the positive square root (standard deviation, S).
874503
['Step 1: Select the period and measurement period over which you wish to calculate the variance. ... ', 'Step 2: Calculate the average return. ... ', 'Step 3: Calculate the difference between each of the individual returns and the average return. ... ', 'Step 4: Calculate the square of the differences and add them all up.']
1163923
['To calculate the sample standard deviation, use formulas in this category: STDEV. S, STDEVA, and STDEV.', 'To calculate the standard deviation for an entire population, use formulas in this category: STDEV. P, STDEVPA, and STDEVP.']
662762
Calculating Standard Error of the Mean First, take the square of the difference between each data point and the sample mean, finding the sum of those values. Then, divide that sum by the sample size minus one, which is the variance. Finally, take the square root of the variance to get the SD.
50126
Calculating variance is very similar to calculating standard deviation. Ensure your data is in a single range of cells in Excel. If your data represents the entire population, enter the formula "=VAR. P(A1:A20)." Alternatively, if your data is a sample from some larger population, enter the formula "=VAR.
1226959
['Mean = Sum_of_each_individual/Total_number_of_items.', 'Variance = ((Original_Value – Mean)² + (Original_Value – Mean)² +.... )/(Total_number_of_items - 1)', 'Standard_Deviation = Square_root (Variance)']