Differentially Private Confidence Intervals for Proportions under Stratified Random Sampling

arXiv:2301.08324v2 Announce Type: replace-cross
Abstract: Confidence intervals are a fundamental tool for quantifying the uncertainty of parameters of interest. With the increase of data privacy awareness, developing a private version of confidence intervals has gained growing attention from both statisticians and computer scientists. Differential privacy is a state-of-the-art framework for analyzing privacy loss when releasing statistics computed from sensitive data. Recent work has been done around differentially private confidence intervals, yet to the best of our knowledge, rigorous methodologies on …

art arxiv attention awareness computer cs.cr data data privacy differential privacy framework interest privacy private random state stat.me tool uncertainty under version