Final answer:
Mean Absolute Deviation represents the average distance between each data point and the mean of the data set, expressed as a positive number. It combines the mean, absolute value, and deviation to provide a measure of spread within a data set.
Step-by-step explanation:
The Mean Absolute Deviation (MAD) is a measure used in statistics to show how much the values in a data set vary or deviate from their mean (average).
The mean is the average of a set of numbers, calculated by adding all the numbers together and then dividing by the count of the numbers. The mean serves to find the central tendency of the data set.
The term absolute value refers to the distance of a number from zero on a number line, without considering direction. Absolute value is always a positive number or zero, as it represents the magnitude of a number.
Deviation represents the distance of an individual data point from the mean of the data set. It shows how much each value differs from the mean.
Calculating the Mean Absolute Deviation involves several steps:
- Compute the mean of the data set.
- Calculate the deviation of each data point from the mean by subtracting the mean from each value.
- Take the absolute value of each deviation to eliminate any negative signs.
- Average these absolute values to get the MAD by adding them up and dividing by the number of values in the data set.