MAD, Standard Deviation, Variance

Front

What is the Mean Absolute Deviation (MAD)?

Back

The Mean Absolute Deviation (MAD) is a measure of the average distance between each data value and the mean of the dataset.

Front

How is the Mean Absolute Deviation calculated?

Back

To calculate MAD, find the mean of the data set, then subtract the mean from each data value, take the absolute value of each result, and finally, find the average of those absolute values.

Front

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

Back

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

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

Back

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

Front

What is standard deviation?

Back

Standard deviation is a measure of the amount of variation or dispersion in a set of values.

Front

How is standard deviation different from Mean Absolute Deviation?

Back

While both measure variability, standard deviation squares the differences from the mean before averaging, which gives more weight to larger differences.

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What is variance?

Back

Variance is the average of the squared differences from the mean, and it is the square of the standard deviation.

Front

How do you calculate variance?

Back

To calculate variance, find the mean of the dataset, subtract the mean from each data value, square the result, and then average those squared values.

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What is the relationship between standard deviation and variance?

Back

Standard deviation is the square root of variance.

Front

What is the formula for calculating the Mean Absolute Deviation?

Back

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