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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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โˆ™ 2013-04-12 19:01:57
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โˆ™ 2013-04-12 19:01:57

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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