Mean Absolute Deviation

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What is Mean Absolute Deviation (M.A.D.)?

Back

Mean Absolute Deviation (M.A.D.) is a measure of the dispersion or variability of a set of data points. It is calculated by taking the average of the absolute differences between each data point and the mean of the data set.

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How do you calculate the Mean Absolute Deviation?

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1. Find the mean of the data set. 2. Subtract the mean from each data point and take the absolute value of each result. 3. Find the average of these absolute values.

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What does a higher Mean Absolute Deviation indicate?

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A higher Mean Absolute Deviation indicates greater variability or spread in the data set.

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What does a lower Mean Absolute Deviation indicate?

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A lower Mean Absolute Deviation indicates that the data points are closer to the mean, showing less variability.

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If the M.A.D. of a data set is 0, what does that mean?

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If the M.A.D. is 0, it means all data points are identical and there is no variability.

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Given the data set 9, 7, 11, 10, 8, what is the Mean Absolute Deviation?

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The Mean Absolute Deviation is 1.2.

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What is the relationship between Mean and Mean Absolute Deviation?

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The Mean is the average of a data set, while the Mean Absolute Deviation measures how much the data points deviate from that average.

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How can you compare the variability of two data sets using M.A.D.?

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You can compare the M.A.D. values of the two data sets; the one with the higher M.A.D. has more variability.

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What is the formula for calculating M.A.D.?

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M.A.D. = (1/n) * Σ|xi - mean|, where n is the number of data points and xi represents each data point.

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What does a dot plot show in relation to M.A.D.?

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A dot plot visually represents data points, allowing you to see the spread and variability, which can help in comparing M.A.D. between different data sets.