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Q: What is the Sum of deviation from the mean is?

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What is mean deviation and why is quartile deviation better than mean deviation?

Information is not sufficient to find mean deviation and standard deviation.

No, a standard deviation or variance does not have a negative sign. The reason for this is that the deviations from the mean are squared in the formula. Deviations are squared to get rid of signs. In Absolute mean deviation, sum of the deviations is taken ignoring the signs, but there is no justification for doing so. (deviations are not squared here)

A set of numbers will have a mean, which is defined as the sum of all the values divided by the number of values. Suppose this mean is m. For each of the values, the squared deviation is the square of the difference between that value and m. Algebraicly, if you have a set {x1, x2, x3, ... , xn}, whose mean is m, then the squared deviation from the mean for x1 is (x1 - m)2.

Standard deviation can be greater than the mean.

Related questions

It is zero.

Mean absolute deviation = sum[|x-mean(x)|]/n Where mean(x) = sum(x)/n and n is the number of observations. |y| denotes the absolute value of y.

* * * * *No it is not.Step 1: Calculate the mean = sum of observations/number of observations.Step 2: For each observation, x, calculate deviation = x - mean.Step 3: Sum together the NON_NEGATIVE values of the above deviations.Step 4: Divide by the number of observations.That is the mean absolute deviation, not the rubbish given below!

Sum of squares of deviations from the mean is small.

The mean deviation or absolute mean deviation is the sum of the differences between data values and the mean, divided by the count. In this case the MAD is 6.

What is mean deviation and why is quartile deviation better than mean deviation?

The variance.

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}

The mean absolute deviation is the sum of the differences between data values and the mean, divided by the count. In this case it is 15.7143

None.The mean of a single number is itself.Therefore deviation from the mean = 0Therefore absolute deviation = 0Therefore mean absolute deviation = 0None.The mean of a single number is itself.Therefore deviation from the mean = 0Therefore absolute deviation = 0Therefore mean absolute deviation = 0None.The mean of a single number is itself.Therefore deviation from the mean = 0Therefore absolute deviation = 0Therefore mean absolute deviation = 0None.The mean of a single number is itself.Therefore deviation from the mean = 0Therefore absolute deviation = 0Therefore mean absolute deviation = 0

No. The mean deviation is 0. Always.

zero

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