Duplicate Question
The question on this page has been marked as a duplicate question.
Original Question
mean absolute deviation ?Asked by Alto Saxophone
mean absolute deviation
Answers
There are no human answers yet.
Answered by
GPT-4o mini
Mean Absolute Deviation (MAD) is a measure of the dispersion or variability in a dataset. It indicates how much individual data points deviate from the mean of the dataset, on average. MAD is particularly useful because it provides a clear and intuitive measure of variability without being affected by outliers, as it considers absolute values.
### How to Calculate Mean Absolute Deviation:
1. **Find the Mean**: Calculate the mean (average) of the data set.
\[
\text{Mean} (\mu) = \frac{\sum_{i=1}^{n} x_i}{n}
\]
where \(x_i\) represents each individual data point and \(n\) is the total number of data points.
2. **Calculate Deviations**: For each data point, calculate the absolute deviation from the mean:
\[
|x_i - \mu|
\]
3. **Mean of Absolute Deviations**: Finally, calculate the mean of these absolute deviations:
\[
\text{MAD} = \frac{\sum_{i=1}^{n} |x_i - \mu|}{n}
\]
### Example:
Consider the following data set: \( [2, 4, 4, 4, 5, 5, 7, 9] \)
1. Calculate the mean:
\[
\mu = \frac{2 + 4 + 4 + 4 + 5 + 5 + 7 + 9}{8} = \frac{40}{8} = 5
\]
2. Calculate the absolute deviations:
- |2 - 5| = 3
- |4 - 5| = 1
- |4 - 5| = 1
- |4 - 5| = 1
- |5 - 5| = 0
- |5 - 5| = 0
- |7 - 5| = 2
- |9 - 5| = 4
3. Calculate the MAD:
\[
\text{MAD} = \frac{3 + 1 + 1 + 1 + 0 + 0 + 2 + 4}{8} = \frac{12}{8} = 1.5
\]
### Interpretation:
In this example, the mean absolute deviation is 1.5, indicating that, on average, the individual data points deviate from the mean by 1.5 units.
MAD is widely used in statistics and data analysis, particularly in fields such as finance, engineering, and environmental science, where understanding variability is crucial.
### How to Calculate Mean Absolute Deviation:
1. **Find the Mean**: Calculate the mean (average) of the data set.
\[
\text{Mean} (\mu) = \frac{\sum_{i=1}^{n} x_i}{n}
\]
where \(x_i\) represents each individual data point and \(n\) is the total number of data points.
2. **Calculate Deviations**: For each data point, calculate the absolute deviation from the mean:
\[
|x_i - \mu|
\]
3. **Mean of Absolute Deviations**: Finally, calculate the mean of these absolute deviations:
\[
\text{MAD} = \frac{\sum_{i=1}^{n} |x_i - \mu|}{n}
\]
### Example:
Consider the following data set: \( [2, 4, 4, 4, 5, 5, 7, 9] \)
1. Calculate the mean:
\[
\mu = \frac{2 + 4 + 4 + 4 + 5 + 5 + 7 + 9}{8} = \frac{40}{8} = 5
\]
2. Calculate the absolute deviations:
- |2 - 5| = 3
- |4 - 5| = 1
- |4 - 5| = 1
- |4 - 5| = 1
- |5 - 5| = 0
- |5 - 5| = 0
- |7 - 5| = 2
- |9 - 5| = 4
3. Calculate the MAD:
\[
\text{MAD} = \frac{3 + 1 + 1 + 1 + 0 + 0 + 2 + 4}{8} = \frac{12}{8} = 1.5
\]
### Interpretation:
In this example, the mean absolute deviation is 1.5, indicating that, on average, the individual data points deviate from the mean by 1.5 units.
MAD is widely used in statistics and data analysis, particularly in fields such as finance, engineering, and environmental science, where understanding variability is crucial.
Submit Your Answer
We prioritize human answers over AI answers.
If you are human, and you can answer this question, please submit your answer.