OPEN-SOURCE SCRIPT
Z-Score
The z-score (also known as the standard score) measures how many standard deviations a data point is from the mean of a dataset. It helps determine whether a data point is typical or unusual compared to the dataset.
The formula for the z-score is:
z = \frac{x - \mu}{\sigma}
Where:
• x = the value being evaluated
• \mu = the mean of the dataset
• \sigma = the standard deviation of the dataset
Interpretation:
• A positive z-score indicates the data point is above the mean.
• A negative z-score indicates the data point is below the mean.
• A z-score of 0 means the data point is exactly at the mean.
The formula for the z-score is:
z = \frac{x - \mu}{\sigma}
Where:
• x = the value being evaluated
• \mu = the mean of the dataset
• \sigma = the standard deviation of the dataset
Interpretation:
• A positive z-score indicates the data point is above the mean.
• A negative z-score indicates the data point is below the mean.
• A z-score of 0 means the data point is exactly at the mean.
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