6.4 Mean Absolute Deviation

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 around the mean. It is calculated by taking the average of the absolute differences between each data point and the mean.

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

What do you do after finding the mean in MAD calculation?

Back

After finding the mean, you find out the distance each number is from the mean.

Front

How do you calculate the absolute difference?

Back

The absolute difference is calculated by subtracting the mean from each data point and taking the absolute value of the result.

Front

What is the formula for calculating MAD?

Back

MAD = (Sum of absolute differences from the mean) / (Number of data points)

Front

If the data set is 10, 9, 3, 8, 10, what is the mean?

Back

The mean of the data set 10, 9, 3, 8, 10 is 8.

Front

Given the data set 58, 38, 54, 48, 26, 36, what is the MAD?

Back

The MAD for the data set 58, 38, 54, 48, 26, 36 is 10.

Front

What is the third step in calculating MAD?

Back

The third step in calculating MAD is to divide the sum of the absolute differences by the number of data points.

Front

Find the MAD for the data set: 65, 90, 85, 70, 70, 95, 55.

Back

The MAD for the data set 65, 90, 85, 70, 70, 95, 55 is 12.24.

Front

What does a lower MAD indicate about a data set?

Back

A lower MAD indicates that the data points are closer to the mean, suggesting less variability.