Math and Arithmetic
Statistics

What is considered measures of variabilty is it mean interquartile range or mean absolute deviation?

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2013-01-15 12:14:37

interquartile range or mean absolute deviation.

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The answer depends on the purpose. The interquartile range and the median absolute deviation are both measures of spread. The IQR is quick and easy to find whereas the MAD is not.

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

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.

Because otherwise it would not be the mean absolutedeviation!

There is no single function in Excel.You calculate the mean (average).For each observation, you calculate its deviation from the mean.Convert the deviation to absolute deviation.Calculate the mean (average) of these absolute deviations.

The range and mean absolute deviation are: Range = 29 Mean absolute deviation = 8.8

If I have understood the question correctly, despite your challenging spelling, the standard deviation is the square root of the average of the squared deviations while the mean absolute deviation is the average of the deviation. One consequence of this difference is that a large deviation affects the standard deviation more than it affects the mean absolute deviation.

no the standard deviation is not equal to mean of absolute distance from the mean

No. Mean absolute deviation is usually greater than 0. It is 0 only if all the values are exactly the same - in which case there is no point in calculating a deviation! The average deviation is always (by definition) = 0

It is 0. A single number, such as 12345678910 has no deviation.

The mean deviation of any set of numbers is always zero and so the absolute mean deviation is also always zero.

The average mean absolute deviation of a data set is the average of the absolute deviations from a central point. It is a summary statistic of statistical dispersion or variability.

absolute deviation is a difference between say two numbers. The result has the same units as the two numbers have. Relative deviation is a ratio and so it is a pure number without any units.

The absolute deviation of 10, 7, 13, 10, 8 is 9.6.

The mean absolute deviation for a set of data is a measure of the spread of data. It is calculated as follows:Find the mean (average) value for the set of data. Call it M.For each observation, O, calculate the deviation, which is O - M.The absolute deviation is the absolute value of the deviation. If O - M is positive (or 0), the absolute value is the same. If not, it is M - O. The absolute value of O - M is written as |O - M|.Calculate the average of all the absolute deviations.One reason for using the absolute value is that the sum of the deviations will always be 0 and so will provide no useful information. The mean absolute deviation will be small for compact data sets and large for more spread out data. The mean absolute deviation for a set of data is a measure of the spread of data. It is calculated as follows:Find the mean (average) value for the set of data. Call it M.For each observation, O, calculate the deviation, which is O - M.The absolute deviation is the absolute value of the deviation. If O - M is positive (or 0), the absolute value is the same. If not, it is M - O. The absolute value of O - M is written as |O - M|.Calculate the average of all the absolute deviations.One reason for using the absolute value is that the sum of the deviations will always be 0 and so will provide no useful information. The mean absolute deviation will be small for compact data sets and large for more spread out data. The mean absolute deviation for a set of data is a measure of the spread of data. It is calculated as follows:Find the mean (average) value for the set of data. Call it M.For each observation, O, calculate the deviation, which is O - M.The absolute deviation is the absolute value of the deviation. If O - M is positive (or 0), the absolute value is the same. If not, it is M - O. The absolute value of O - M is written as |O - M|.Calculate the average of all the absolute deviations.One reason for using the absolute value is that the sum of the deviations will always be 0 and so will provide no useful information. The mean absolute deviation will be small for compact data sets and large for more spread out data. The mean absolute deviation for a set of data is a measure of the spread of data. It is calculated as follows:Find the mean (average) value for the set of data. Call it M.For each observation, O, calculate the deviation, which is O - M.The absolute deviation is the absolute value of the deviation. If O - M is positive (or 0), the absolute value is the same. If not, it is M - O. The absolute value of O - M is written as |O - M|.Calculate the average of all the absolute deviations.One reason for using the absolute value is that the sum of the deviations will always be 0 and so will provide no useful information. The mean absolute deviation will be small for compact data sets and large for more spread out data.

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