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How do you calculate standard deviation?
standard deviation is the positive square root of mean of the deviations from an arithmatic mean X denoted as sigma.sigma=sqrt {(sum(x-X)^2)/n}
When computing the sample variance the sum of squared deviations about the mean is used for what reason?
You want some measure of how the observations are spread about the mean. If you used the deviations their sum would be zero which would provide no useful information. You could use absolute deviations instead. The sum of squared deviations turns out to have some useful statistical properties including a relatively simple way of calculating it. For example, the Gaussian (or Normal) distribution is completely defined by its mean and variance.
How do u calculate mean absolute deviation?
You calculate the mean.For each observation, you calculate its deviation from the mean.Convert the deviation to absolute deviation.Calculate the mean of these absolute deviations.
In any distribution is the sum of the squared deviations from the mean always equal to zero?
No. It cannot be. Remember that when you square a negative number it becomes a positive number. Thus all squared deviations are positive and their sum must be positive.
What does the sum of the deviations of each value from the mean equal?
The sum will be zero or close to zero, depending on how the sampling was done. See related question.
What is the sum of the deviations from the mean?
The sum of standard deviations from the mean is the error.
The sum of the deviations about the mean always equals what?
The sum of total deviations about the mean is the total variance. * * * * * No it is not - that is the sum of their SQUARES. The sum of the deviations is always zero.
The sum of the deviations from the mean is always zero?
The definition of the mean x of a set of data is the sum of all the values divided by the total number of observations, and this value is in turn subtracted from each x value to calculate the deviations. When the deviations from the average are added up, the sum will always be zero because of the negative signs in the sum of deviations. Going back to the definition of the mean, the equation provided (x = Σxi/n) can be manipulated to read Σxi - x = 0
What does the sum of the deviations from the mean equal?
Zero.
The sum of the deviations from the mean is always?
0 (zero).
The sum of deviations of the individual data elements from their mean is?
zero
How do you calculate standard deviation?
standard deviation is the positive square root of mean of the deviations from an arithmatic mean X denoted as sigma.sigma=sqrt {(sum(x-X)^2)/n}
For which measure of central tendency will the sum of the deviations always be zero?
Mean
How do you subtract standard deviations?
Square the standard deviations, subtract/add them and calculate the square root of the subtraction/sum. StDV=sqrt (StDvA^2+StDvB^2)
What is the Sum of deviation from the mean is?
The sum of deviations from the mean, for any set of numbers, is always zero. For this reason it is quite useless.
What is the sum of the squared deviations from the mean divided by the count minus one?
variation
When computing the sample variance the sum of squared deviations about the mean is used for what reason?
You want some measure of how the observations are spread about the mean. If you used the deviations their sum would be zero which would provide no useful information. You could use absolute deviations instead. The sum of squared deviations turns out to have some useful statistical properties including a relatively simple way of calculating it. For example, the Gaussian (or Normal) distribution is completely defined by its mean and variance.
