Eric Daza | N-of-1 Science & Causal Inference | Philosophy of Data Science

<p>Interesting in Data Science? Learn Data Science and Statistics from experts as they cover key topics in the field. The Data & Science podcast focusses on teaching data scientists how to think critically in order to solve data analysis problems across various scientific domains.</p> <p> </p> <p>Eric Daza | N-of-1 Science & Causal Inference | Philosophy of Data Science</p> <p>Much of our scientific inference revolves around the identification and replication of patterns in data. So what can be done when N=1? Eric Daza gives us a statistician's perspective on the ideas behind N-of-1 studies, its best examples, and strongest critiques.</p> <p> </p> <p>0:00 - The purpose of N-of-1 & generalizability</p> <p>3:30 - Successes and challenges in N-of-1</p> <p>9:30 - A lightbulb moment</p> <p>18:00 – Anomalies, Compliance, & Recurring Patterns</p> <p>23:00 – Best Critiques of N-of-1, Safety, Efficacy</p> <p>41:20 - Causal Inference</p> <p>54:30 – Increasing the number of data scientists</p> <p>1:03:30 – Biostatistics’ changing place in data science / statistical thinking</p>