Do you have to code all documents to estimate richness?

Estimating richness does not require coding all documents in a dataset because sampling techniques can provide a representative view of the overall data characteristics without the need for exhaustive analysis. By coding only a sample set, analysts can extrapolate findings to infer the richness level of the entire dataset. This approach is both time-efficient and resource-effective, enabling teams to gather insights without becoming bogged down in the details of every document.

Focusing on a sample allows for the identification of trends and patterns that would likely be present across the entire project. Furthermore, sampling can enhance speed while maintaining a reasonable level of accuracy in richness estimation. This method is widely recognized in data analytics as a best practice, particularly when dealing with large datasets.

While complexity of documents and project specificities could influence the depth of coding needed, it's generally recognized that a comprehensive coding of every document is unnecessary for an effective richness assessment, making sampling a preferred strategy.