Exploring Mean Absolute Deviation (MAD)

The video tutorial explains how to calculate the mean absolute deviation (MAD) for a data set. It begins by finding the mean of the data set, then calculates the deviation of each data value from the mean. These deviations are converted to absolute values, and the average of these absolute deviations is computed to find the MAD. The process is demonstrated with a specific data set, showing each step in detail.

What is the first step in calculating the mean absolute deviation for a dataset?

• Find the range of the data

• Calculate the mean of the data

• Determine the median of the data

• Identify the mode of the data

If the mean of a dataset is 6, what is the deviation of a data value of 9?

• 3

• -3

• 0

• 6

What transformation is applied to deviations when calculating the mean absolute deviation?

• Multiply each deviation by the mean

• Divide each deviation by the mean

• Take the absolute value of each deviation

• Square each deviation

Why do we use absolute values when calculating the mean absolute deviation?

• To find the median value

• To increase the dataset size

• To simplify the calculations

• To eliminate negative numbers

How do you calculate the mean absolute deviation once you have the absolute deviations?

• Subtract them from the mean

• Multiply them by the number of data points

• Add them and divide by the number of data points

• None of the above

What is the mean absolute deviation if the sum of absolute deviations is 10 and there are 5 data points?

• 2

• 5

• 0.5

• 1.5

Which of the following is a correct step in the process of calculating the mean absolute deviation?

• Averaging the absolute deviations

• Calculating the sum of squared deviations

• Taking the square root of each deviation

• Finding the product of all deviations

What does the mean absolute deviation measure in a dataset?

• Central tendency

• Skewness of the data

• Spread from the median

• Variability around the mean