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Mean Absolute Deviation Explained by Adri versouisse is a document available to read on EtoBox.
The mean absolute deviation is a measure of variability that calculates the average distance between each data point in a dataset and the mean. It is calculated by first finding the mean, then taking the absolute value of the difference between each data point and the mean, summing those absolute differences, and dividing by the number of data points. For a dataset of the number of likes on 666 cat pictures, the mean absolute deviation was approximately 2.67 likes, meaning on average each data point differe
- Author
- Adri versouisse
- Language
- EN