Design of Experiments (4)
- Must Know for Data Scientists and Data Analysts: Causal Design Patterns - Mar 12, 2021.
Industry is a prime setting for observational causal inference, but many companies are blind to causal measurement beyond A/B tests. This formula-free primer illustrates analysis design patterns for measuring causal effects from observational data.
- Design of Experiments in Data Science - Sep 3, 2020.
Read this overview of the process of designing experiments for collecting data.
- Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing - Apr 28, 2020.
The book Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing by Ron Kohavi (Microsoft, Airbnb), Diane Tang (Google) and Ya Xu (LinkedIn) is available for purchase, with the authors proceeds from the book being donated to charity.
- What Does a Lady Tasting Tea Have to Do with Science? - May 31, 2019.
Design of Experiments (DOE) is a statistical concept used to find the cause-and-effect relationships. Surprisingly, an experiment arising from a casual conversation about tea-drinking is one of the first examples of an experiment designed using statistical ideas.