Mean Absolute Deviation (M.A.D)

Front

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

Back

Mean Absolute Deviation (M.A.D) is a measure of the dispersion or spread of a set of data points. It represents the average distance between each data point and the mean of the data set.

Tags

CCSS.6.SP.B.5C

Front

How do you calculate the Mean Absolute Deviation?

Back

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.

Tags

CCSS.6.SP.B.5C

Front

What is the formula for Mean Absolute Deviation?

Back

M.A.D = (Σ |x_i - mean|) / N, where x_i represents each data point, mean is the average of the data set, and N is the number of data points.

Tags

CCSS.6.SP.B.5C

Front

What does the 'absolute' in Mean Absolute Deviation signify?

Back

The 'absolute' means that we take the positive value of the differences between each data point and the mean, ensuring that all deviations are treated equally regardless of direction.

Tags

CCSS.6.SP.B.5C

Front

What is the significance of a low Mean Absolute Deviation?

Back

A low M.A.D indicates that the data points are close to the mean, suggesting less variability in the data set.

Tags

CCSS.6.SP.B.5C

Front

What is the significance of a high Mean Absolute Deviation?

Back

A high M.A.D indicates that the data points are spread out over a wider range, suggesting greater variability in the data set.

Tags

CCSS.6.SP.B.5C

Front

In a data set of 5, 10, 15, 20, what is the Mean Absolute Deviation?

Back

M.A.D = 5.0

Tags

CCSS.6.SP.B.5C

Front

If the Mean of a data set is 50, what does a M.A.D of 10 indicate?

Back

It indicates that, on average, the data points deviate from the mean by 10 units.

Tags

CCSS.6.SP.B.5C

Front

What is the first step in calculating M.A.D?

Back

The first step is to calculate the mean (average) of the data set.

Tags

CCSS.6.SP.B.5C

Front

What is the second step in calculating M.A.D?

Back

The second step is to find the absolute differences between each data point and the mean.

Tags

CCSS.6.SP.B.5C