Mean and Mean Absolute Deviation

Front

What is the Mean Absolute Deviation (MAD)?

Back

The Mean Absolute Deviation (MAD) is a measure of the dispersion of a set of data points. It is calculated as the average of the absolute differences between each data point and the mean of the dataset.

Front

How do you calculate the mean of a dataset?

Back

To calculate the mean, sum all the values in the dataset and then divide by the number of values.

Front

What is the first step in calculating the Mean Absolute Deviation?

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The first step is to find the mean of the data.

Front

What is the second step in calculating the Mean Absolute Deviation?

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The second step is to find the distance each value is from the mean.

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How do you find the absolute deviation of a single data point?

Back

The absolute deviation of a single data point is found by taking the absolute value of the difference between the data point and the mean.

Front

What is the formula for calculating the Mean Absolute Deviation?

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

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What does a low Mean Absolute Deviation indicate about a dataset?

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A low Mean Absolute Deviation indicates that the data points are close to the mean, suggesting low variability.

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What does a high Mean Absolute Deviation indicate about a dataset?

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A high Mean Absolute Deviation indicates that the data points are spread out over a wider range of values, suggesting high variability.

Front

Given the data set 58, 38, 54, 48, 26, 36, what is the Mean Absolute Deviation?

Back

The Mean Absolute Deviation for the dataset is 10.

Front

Given the data set 85, 90, 68, 75, 79, what is the Mean Absolute Deviation?

Back

The Mean Absolute Deviation for the dataset is 6.48.