Abstract
We aim to present a statistician’s and a computer scientist’s perspectives on statistical inference in the context of privacy. We will consider questions of (1) how to perform valid statistical inference using differentially private data or summary statistics, and (2) how to design optimal formal privacy mechanisms and inference procedures. We will discuss what we believe are key theoretical and practical issues and tools. Our examples will include point estimation and hypothesis testing problems and solutions, and synthetic data.