Why is Normal Distribution Important in Epidemiology?
The normal distribution is essential in Epidemiology for several reasons:
Central Limit Theorem: This theorem states that the distribution of sample means will approximate a normal distribution, regardless of the distribution of the population, given a sufficiently large sample size. This is fundamental for making inferences about population parameters based on sample data. Standardization: Many statistical methods, including confidence intervals and hypothesis testing, rely on the assumption of normality. This allows for the standardization and comparison of different datasets. Baseline Comparisons: Normal distribution provides a baseline against which deviations can be measured. It helps in identifying outliers and understanding the spread of data.
