 Welcome to the attribution reporting simulation tools deep dive part one where we will be learning about noise lab. My name is Akash and I'm a product manager on the Privacy Sandbox team and we'll be guiding you through the first half of this deep dive. In this deep dive, we'll start by establishing what the goals and outcomes are. Then we'll do a quick overview of the attribution reporting API followed by a look at how summary reports work and then a quick overview of noise and the various parameters that can change the impact of noise. And then finally, we will jump into noise lab and walk through the various functionality that it provides and go through a couple of real scenarios so you can see the different types of experiments you can run in noise lab. And finally, we'll finish up with a Q&A and links to where you can find additional documentation. The goal of this presentation is that by the end of the deep dive, you have developed a strong understanding of what noise is and why it is needed for privacy as well as how various parameters impact noise and how they can be changed. And then finally, how noise lab can be used to assess the impact of noise as well as for experimenting on different ad tech scenarios.