Sample Variance

Sample variance, a measure of data spread crucial for statistical inference, is undergoing renewed scrutiny, particularly in contexts beyond simple ground truth comparisons. Current research focuses on accurately estimating sample variance in complex settings, such as model-based evaluations (e.g., using a toxicity classifier to compare language models) and within neural network architectures like Mean Variance Estimation networks. These advancements aim to improve the reliability of statistical significance testing and uncertainty quantification in diverse fields, impacting the validity of conclusions drawn from data analysis across numerous scientific disciplines and applications.

Papers