Missing values refer to any data entry that is missing or incomplete in a dataset. This can occur for a variety of reasons such as data entry errors, equipment malfunctions, or non-response from survey participants. Dealing with missing values is a common problem in data analysis and can have a significant impact on the results of statistical analyses. Researchers often employ various techniques such as imputation or deletion to handle missing data and ensure the validity and reliability of their findings.