Easy.
The mean deviation about the mean, for any distribution, MUST be 0.
They are measures of the spread of distributions about their mean.
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.
Various answers to this question are possible.The mean absolute deviation (MAD) is a measure of the dispersion or spread of a sample or a population. So one of its purposes is as a measure.As such it's an alternative to the standard deviation that is said to be more robust in the sense that the sample MAD can be used to provide more accurate estimates of the population dispersion because it is less sensitive to outliers.Beyond this, some distributions that have no standard deviations do have MADs; for example, the Cauchy. This means that the dispersions of virtually all distributions can be compared in terms of their MADs.Please see the link.
The mean average deviation is the same as the mean deviation (or the average deviation) and they are, by definition, 0.
The total deviation from the mean for ANY distribution is always zero.
To derive the mean of generalized Pareto distribution you must be good with numbers. You must be good in Calculus, Algebra and Statistics.
They are measures of the spread of distributions about their mean.
the sample mean is used to derive the significance level.
A family that is defined by two parameters: the mean and variance (or standard deviation).
No, and no. Think about two skewed distributions that are mirrored across the mean so that one is right and one is left. they have the same mean and standard deviation, but are opposite. Also, the 5 number summary does not affect a histogram
Standard deviation is a measure of the dispersion of the data. When the standard deviation is greater than the mean, a coefficient of variation is greater than one. See: http://en.wikipedia.org/wiki/Coefficient_of_variation If you assume the data is normally distributed, then the lower limit of the interval of the mean +/- one standard deviation (68% confidence interval) will be a negative value. If it is not realistic to have negative values, then the assumption of a normal distribution may be in error and you should consider other distributions. Common distributions with no negative values are gamma, log normal and exponential.
What is mean deviation and why is quartile deviation better than mean deviation?
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.
Various answers to this question are possible.The mean absolute deviation (MAD) is a measure of the dispersion or spread of a sample or a population. So one of its purposes is as a measure.As such it's an alternative to the standard deviation that is said to be more robust in the sense that the sample MAD can be used to provide more accurate estimates of the population dispersion because it is less sensitive to outliers.Beyond this, some distributions that have no standard deviations do have MADs; for example, the Cauchy. This means that the dispersions of virtually all distributions can be compared in terms of their MADs.Please see the link.
The mean average deviation is the same as the mean deviation (or the average deviation) and they are, by definition, 0.