A z-score measures how far a data point is from the mean, expressed in terms of standard deviations, helping to identify outliers and compare data distributions.
To calculate z-scores in Python, you can define a custom function that takes a vector of values along with their mean and standard deviation.
Using historical datasets, such as Playfair's collection of wheat prices and wages, helps illustrate the practical application of z-scores in analyzing economic well-being.
Visualizing z-scores can enhance understanding and interpretation, making it easier to analyze how individual data points relate to the overall dataset.
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