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Bootstrapping the Right Way

YOW! Data 2019

Bootstrap sampling is being touted as a simple technique that any hacker can easily employ to quantify the uncertainty of statistical estimates. However, despite its apparent simplicity, there are many ways to misuse bootstrapping and thereby draw wrong conclusions about your data and the world. This talk gives a brief overview of bootstrap sampling and discusses ways to avoid common pitfalls when bootstrapping your data.

Yanir Seroussi

Distinguished Data Scientist



Yanir is an experienced data scientist and software engineer with a strong background in computer science, programming, machine learning, and statistics. His work spans the full spectrum from solving isolated data problems to building production systems that serve millions of users. He has produced top results in various areas such as recommender systems, text mining, price forecasting, and personalisation. Examples include: ranking highly as a Kaggle Master, producing award-winning PhD work, and implementing live systems that substantially increase revenue through smart use of data. He currently works remotely as a data scientist with Automattic, the company behind and one of the world's largest fully-distributed employers.