When is a statistical sample set not recommended?

A statistical sample set is not recommended when the data set is not large enough, specifically when it contains fewer than 300 documents. This is because small sample sizes can lead to unreliable and non-representative results. In statistics, larger sample sizes are preferred as they tend to provide a better approximation of the population, reducing the impact of anomalies or outliers in the data. When the sample is too small, it may not capture the full variability present in the larger population, making it challenging to draw accurate conclusions or make informed decisions based on the data.

In contrast, having a data set with more than 1000 documents could actually bolster the statistical analysis, and grouped documents in different categories might still yield valuable insights if analyzed appropriately. Archived documents may pose challenges for access or processing but do not inherently invalidate the potential for statistical sampling, assuming the quantity is adequate. Therefore, maintaining a minimum threshold of documents is crucial for effective statistical sampling.