zscoring
Zscoring, or standardization, is a data transformation that rescales a dataset so that its distribution has a mean of zero and a standard deviation of one. For an observation x in a dataset with mean μ and standard deviation σ, the z-score is defined as z = (x − μ)/σ. When computed from a sample, μ is typically the sample mean x̄ and σ the sample standard deviation s. If the data are approximately normally distributed, z-scores map onto the standard normal distribution N(0,1), allowing probabilities and percentiles to be read from the standard normal table.
Z-scores provide a unitless measure of how many standard deviations an observation lies from the mean, enabling
Important considerations include the dependence on the estimated mean and standard deviation. Z-scores assume the data