Join Andrew Gelman, a statistics and political science professor at Columbia, Jennifer Hill from NYU specializing in causal questions, and Aki Vehtari, an expert in computational modeling from Aalto University, as they dive into the enchanting world of regression analysis. They share insights on their writing journey, offer ten tips to enhance regression modeling, tackle the challenges of statistical significance, and reveal the power of storytelling in data education. Plus, there's a whimsical discussion about exploring Mars!

Associate professor Aki Vehtari discusses model assessment, non-parametric models like Gaussian processes, and Bayesian probability theory. He talks about teaching Bayesian statistics, open-source software development, and his work on a software-assisted Bayesian workflow. Vehtari shares insights on overcoming challenges in data analysis, model selection, and the dynamic nature of research in the field.