What is the effect of increasing the number of reviewed documents in relation to validation statistics?

Increasing the number of reviewed documents positively impacts validation statistics by enabling better bias reduction. When more documents are included in the review process, the diversity and representation of the dataset improve, leading to a more comprehensive understanding of the data and its characteristics. This broadens the sampling, helping to identify and mitigate any potential biases that might exist within the data.

Improving bias reduction is crucial because it increases the reliability of the analytics outcomes and enhances the overall quality of the validation process. As biases are minimized, the findings become more accurate and valid, directly improving the effectiveness of the analytics efforts.

In contrast, while other effects such as changes to recall or precision can occur with varying numbers of reviewed documents, these are less direct consequences than the enhancement of bias reduction that results from a larger sample size.