Super Data Science: ML & AI Podcast with Jon Krohn cover image

607: Inferring Causality

Super Data Science: ML & AI Podcast with Jon Krohn

CHAPTER

Understanding Causal Questions and Inference

The chapter explores the significance of causal questions in decision-making across various contexts, from personal choices to scientific research, emphasizing the need to rely on controlled studies for accurate conclusions. It delves into the complexities of causal inference, discussing the challenges individuals face in drawing global causal conclusions and the importance of considering counterfactual scenarios. Additionally, the chapter addresses common misconceptions like confusing correlation with causation and the role of media sensationalism in exacerbating these issues.

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