Mean Absolute Deviation Practice

Front

What is Mean Absolute Deviation (MAD)?

Back

Mean Absolute Deviation (MAD) is a measure of the dispersion or spread 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.

Front

How do you calculate the mean of a data set?

Back

To calculate the mean, add all the numbers in the data set together and then divide by the total number of values.

Front

What is the first step in calculating MAD?

Back

The first step in calculating MAD is to find the mean (average) of the data set.

Front

After finding the mean, what is the next step in calculating MAD?

Back

The next step is to find the absolute difference between each data point and the mean.

Front

What do you do with the absolute differences when calculating MAD?

Back

You take the average of the absolute differences to find the Mean Absolute Deviation.

Front

If the data set is 10, 12, 14, 16, what is the mean?

Back

The mean is 13.

Front

Given the data set 5, 10, 15, 20, what is the MAD?

Back

The MAD is 5.

Front

What does a low MAD indicate about a data set?

Back

A low MAD indicates that the data points are close to the mean, showing less variability.

Front

What does a high MAD indicate about a data set?

Back

A high MAD indicates that the data points are spread out over a wider range of values, showing more variability.

Front

In the context of MAD, what does 'absolute' mean?

Back

'Absolute' refers to the non-negative value of the differences, meaning we ignore whether the difference is positive or negative.