While z scores are powerful tools, they have limitations:
Assumption of Normality: Z scores assume that the data follows a normal distribution, which may not always be the case. Sensitivity to Outliers: Extreme outliers can distort the mean and standard deviation, thus affecting z scores. Interpretation: Misinterpretation of z scores can lead to incorrect conclusions, especially if the underlying data is not well understood.
