Comparing Absolute Deviation to Mean Absolute Deviation

In summary, the speaker is trying to measure variability in a part for their sensor and has decided to use precision as a way to do so. They are wondering if they can compare absolute deviation and mean absolute deviation to calculate a percentage deviation, which can then indicate the variability in the part. They have also mentioned calculating 15 absolute deviations and their mean absolute deviation and asked if it would be valid to say their data set is accurate if all 15 absolute deviations are within ±5% of the mean absolute deviation. The speaker is using nuclear counting for medical imaging and does not know the true estimate of counts for their system, so they are measuring precision to see if their system is operating consistently as they change a certain part.
  • #1
Nyasha
127
0
Hi Guys,

I am trying to measure variability in a part for my sensor which l do not know the true value. So l decided that a good way to measure variability in this case would be to measure precision of my data points as l change this part on the sensor. So l was wondering, can l compare the absolute deviation and mean absolute deviation and calculate the percentage deviation between the two, and then use the percentage deviation as a number which tells me something about variability in this part.


Thanks.
 
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  • #2
Your description is not very clear. Please flesh it out more, perhaps with an example.
 
  • #3
haruspex said:
Your description is not very clear. Please flesh it out more, perhaps with an example.

I calculated 15 absolute deviations and their mean absolute deviation. Would it be valid for me to say my data set is accurate if all the 15 absolute deviations are within ±5% of the mean absolute deviation ?
 
  • #4
No, I meant a much more thorough description of what you are doing. What do you mean by "measuring the precision"? What does this involve? What, arithmetically, do you then do with the observations?
 
  • #5
I am doing nuclear counting for medical imaging and l do not know the 'true' estimate of counts for my system. So to see if my system is operating consistently as l change a certain part, l am going to measure its precision. That is, as l change that part, are my number of counts within the same range.
 

What is the difference between absolute deviation and mean absolute deviation?

Absolute deviation is a measure of how far a data point is from the mean of a data set, regardless of its direction. Mean absolute deviation, on the other hand, is the average of all the absolute deviations in a data set, giving a more balanced representation of the overall variability of the data.

How are absolute deviation and mean absolute deviation calculated?

Absolute deviation is calculated by finding the difference between each data point and the mean, taking the absolute value of each difference, and then finding the average of these absolute values. Mean absolute deviation is calculated by finding the absolute deviation of each data point, adding them together, and then dividing by the total number of data points.

Which measure of variability is more affected by extreme values: absolute deviation or mean absolute deviation?

Mean absolute deviation is more affected by extreme values because it takes into account all the data points, including the outliers. Absolute deviation only considers the distance from the mean, so extreme values may not have as big of an impact on its calculation.

When would you use absolute deviation over mean absolute deviation?

Absolute deviation is a useful measure when you want to understand the spread of data without being influenced by extreme values. It can also be used when the data set is small and does not require a more precise measure of variability.

How do you interpret the values of absolute deviation and mean absolute deviation?

The values of absolute deviation and mean absolute deviation give an indication of the variability or spread of a data set. A higher value indicates that the data points are more spread out from the mean, while a lower value indicates a more concentrated data set. Mean absolute deviation may be more useful when comparing the variability between different data sets since it is calculated as an average.

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