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The mean is the sum of each sample divided by the number of samples.
The median is the middle sample in a ranked list of samples, or the mean of the middle two samples if the number of samples is even.
The standard deviation is the square root of the sum of the squares of the difference between the mean and each of the samples, such sum then divided by either N or by N-1, before the square root is taken. N is used for population standard deviation, where the mean is known independently of the calculation of the standard deviation. N-1 is used for sample standard deviation, where the mean is calculated along with the standard deviation, and the "-1" compensates for the loss of a "degree of freedom" that such a procedure entails.
Not asked, but answered for completeness sake, the mode is the most probable value, and does not necessarily represent the mean such as in an asymmetrically skewed distribution, such as a Poisson distribution.
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How do mean deviation from median?
The mean deviation from the median is equal to the mean minus the median.
Which of the following is least affected if an extreme high outlier is added to your data mean median or standard deviation or ALL?
The median is least affected by an extreme outlier. Mean and standard deviation ARE affected by extreme outliers.
How do you calculate standard deviation with the help of z-score?
A z-score cannot help calculate standard deviation. In fact the very point of z-scores is to remove any contribution from the mean or standard deviation.
How do you calculate the standard deviation of the mean using Excel?
=stdev(...) will return the N-1 weighted sample standard deviation. =stdevp(...) will return the N weighted population standard deviation.
If mean is 8 median is 6 and standard deviation is 2 what is skewness?
Karl Pearson simplified the topic of skewness and gave us some formulas to help. The first is the Pearson mode or first skewness coefficient. It is defined by the (mean-median)/standard deviation. So in this case the Pearson mode is: (8-6)/2 =1 There is also the Pearson Median. This is also called second skewness coefficient. It is defined as 3(mean-median)/standard deviation which in this case is 6/2 =3 hence the distribution is positive skewed
