Z scores are crucial in epidemiology for several reasons:
Standardization: They allow for the comparison of different datasets by converting values to a common scale. Outlier Detection: Z scores can identify outliers, which may indicate errors or significant findings. Risk Assessment: They help in assessing risk factors by comparing individual scores to population averages. Hypothesis Testing: Z scores are often used in statistical tests to determine the significance of results.
