how to calculate sample standard deviation of differences?
11944
['Work out the Mean (the simple average of the numbers)', 'Then for each number: subtract the Mean and square the result.', 'Then work out the mean of those squared differences.', 'Take the square root of that and we are done!']
340037
['Step 1: Calculate the mean (the average weight).', 'Step 2: Subtract the mean and square the result.', 'Step 3: Work out the average of those differences.']
1082092
First multiply the critical value by the standard deviation. Then divide this result by the error from Step 1. Now square this result. This result is the sample size.
541784
['Step 1: Calculate the mean of the data—this is μ in the formula.', 'Step 2: Subtract the mean from each data point. ... ', 'Step 3: Square each deviation to make it positive.', 'Step 4: Add the squared deviations together.', 'Step 5: Divide the sum by the number of data points in the population.']
245669
['Estimating the standard deviation, σ, of the sample data.', 'Multiplying that number by three.', 'Adding (3 x σ to the average) for the UCL and subtracting (3 x σ from the average) for the LCL.']
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.
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).
645103
The standard deviation is given by the square root of the variance. To find the variance, we first calculate the mean of the set of data. Next, we subtract the mean from each number in the data set and square the results. Then, we take the average of the squared differences.
760743
You can calculate standard error for the sample mean using the formula: SE = s/√(n) SE = standard error, s = the standard deviation for your sample and n is the number of items in your sample.
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.']
963714
['Calculate the mean of your data set.', 'Subtract that mean from each of the scores in your data set to determine the individual deviation of each score from the mean.', 'Square each of those individual deviations.', 'Sum all of the squared deviations.', 'Divide that sum by one less than the sample size (N–1)']
513195
['Calculate the mean, x.', 'Write a table that subtracts the mean from each observed value.', 'Square each of the differences.', 'Add this column.', 'Divide by n -1 where n is the number of items in the sample This is the variance.']
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.']
43171
['Step 1: Calculate the mean of the data—this is xˉx, with, \\bar, on top in the formula.', 'Step 2: Subtract the mean from each data point. ... ', 'Step 3: Square each deviation to make it positive.', 'Step 4: Add the squared deviations together.']
1274294
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.
399889
Step 1: Calculate the mean (Total of all samples divided by the number of samples). Step 2: Calculate each measurement's deviation from the mean (Mean minus the individual measurement). ... Step 7: Divide the standard deviation by the square root of the sample size (n). That gives you the “standard error”.
309084
The formula for standard deviation is sqrt([sample size][probability of success](1-[probability of success])). To find the sample size from the mean and success rate, you divide the mean by the success rate. If mean=10 and success=0.2, you do 10/0.2 to get your sample size, or 50 in this case.