{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/6f85ca0a778d4a14ae0b0a8befe903a7\" frameborder=\"0\" width=\"1114\" height=\"835\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":835,"width":1114,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":835,"thumbnail_width":1114,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/6f85ca0a778d4a14ae0b0a8befe903a7-bca210ffdddca4f1.gif","duration":133.8623,"title":"Lecture 1 - 1.2","description":"In 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."}