Steve's Data Tips and Tricks provides a comprehensive guide to using the na.omit() function in R to manage missing values effectively in vectors, matrices, and data frames. Missing values, often represented as "NA", can arise from various issues such as data collection errors and incomplete surveys, which can adversely affect statistical calculations, model accuracy, and data visualisation. The guide explains the basic usage of the na.omit() function, its syntax, and how it can be applied to vectors and data frames for removing incomplete cases. It offers practical examples, advanced applications like conditional removal, and best practices, such as backing up original data and considering the implications of data removal. The guide addresses FAQs, highlighting that while na.omit() is effective, alternative methods exist for handling missing values, and ultimately emphasises the importance of documenting strategies for managing NA values in data analysis.