Missing Data

Missing data refers to gaps in a dataset where information was not recorded or isn't available. This can happen for various reasons, such as respondents skipping questions or data entry errors. Missing data can affect analysis because it limits the completeness of the information, potentially leading to biased or less accurate results. In handling missing data, researchers often use techniques like imputation (estimating missing values) or excluding incomplete records, depending on the situation. Addressing missing data thoughtfully is essential for ensuring valid and reliable conclusions.