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.

Tags

CCSS.6.SP.B.5C

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.

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CCSS.6.SP.B.5C

Front

What is the first step in calculating MAD?

Back

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

Tags

CCSS.6.SP.B.5C

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.

Tags

CCSS.6.SP.B.5C

Front

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

Back

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

Tags

CCSS.6.SP.B.5C

Front

If the data set is {2, 4, 6, 8}, what is the mean?

Back

The mean is (2 + 4 + 6 + 8) / 4 = 5.

Tags

CCSS.6.SP.B.5C

Front

If the mean of a data set is 5, what is the absolute difference of the data point 8?

Back

The absolute difference is |8 - 5| = 3.

Tags

CCSS.6.SP.B.5C

Front

What is the formula for calculating Mean Absolute Deviation?

Back

MAD = (|x1 - mean| + |x2 - mean| + ... + |xn - mean|) / n, where x1, x2, ..., xn are the data points and n is the number of data points.

Tags

CCSS.6.SP.B.5C

Front

Why is it important to use absolute values when calculating MAD?

Back

Using absolute values ensures that all differences are positive, allowing for a true average of the distances from the mean.

Tags

CCSS.6.SP.B.5C

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, suggesting less variability.

Tags

CCSS.6.SP.B.5C