video1.0<iframe src="https://www.loom.com/embed/6f85ca0a778d4a14ae0b0a8befe903a7" frameborder="0" width="1114" height="835" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>8351114Loomhttps://www.loom.com8351114https://cdn.loom.com/sessions/thumbnails/6f85ca0a778d4a14ae0b0a8befe903a7-bca210ffdddca4f1.gif133.8623In this video, I discuss the importance of causal inference in making smarter decisions across various sectors, such as pharmaceuticals, public policy, marketing, finance, and technology. I provide examples like evaluating a new drug for chronic pain, assessing the impact of a sugar tax on obesity rates, and determining the effectiveness of a new email campaign. Each scenario highlights the critical decision questions we face, such as whether a specific intervention leads to desired outcomes. I encourage viewers to consider how causal inference can inform their own decision-making processes. Let's leverage data to drive better results in our respective fields.