Statistical Data Cleaning With Applications In R -

The authors emphasize that data cleaning is not just about removing errors but about identifying them through . Statistical Data Cleaning with Applications in R

Central to the authors' philosophy is the concept of the . This framework views data processing as a series of steps that increase the data’s value: Raw Data: The initial, unrefined input. Statistical Data Cleaning with Applications in R

Data that has been checked against domain-specific rules and logical restrictions. Key Methodology and R Applications The authors emphasize that data cleaning is not

Data with consistent types (e.g., numeric, character) and structures (e.g., tidy tables). character) and structures (e.g.