Data interpretation in epidemiology involves several steps and techniques to ensure valid and reliable conclusions: - Descriptive Analysis: Summarizes the data using measures of central tendency (mean, median) and dispersion (range, standard deviation). - Inferential Analysis: Uses statistical methods to make inferences about the population based on sample data. This includes hypothesis testing, confidence intervals, and regression analysis. - Bias and Confounding: Epidemiologists must account for potential biases (selection, information) and confounders that could distort their findings. Techniques such as stratification and multivariable analysis help to mitigate these issues.
