The quality of content in ACI is due to the rigor of our selection process and to the incredible scholarship and credentials of scholarly bloggers publishing in their fields. Due to this selectivity in content and academic contributions, ACI is proud to highlight exceptional blog authors in order to showcase their work and inspire other authors… and today’s author spotlight is on Dr. Andrew Gelman.

Dr. Gelman is currently a Professor in Statistics and Political Science at Columbia University, as well as a Visiting Professor in Statistics at Harvard University. He received his PhD and MA in Statistics from Harvard after having earned a BA in statistics and math at MIT.

With awards from both statistics and political science organizations, he (along with a handful of occasional contributors) tackles both subjects – and a number of other topics – in his blog, Statistical Modeling, Causal Inference, and Social Science.

Dr. Gelman describes how he came to focus on statistics and political science for his academic career, a process that began in his early days as an undergraduate and nurtured by the multidisciplinary nature of his interests.

“I majored in math and physics in college and minored in political science,” he explains. “I chose to become a statistician partly because I did not see myself as an exceptional mathematician or physicist, and partly because statistics connects to all of my interests, including the natural and social sciences.”

However, in addition to his primary fields of statistics and political science, his research interests also include such topics as toxicology, medical imaging, econometrics, crime-related issues, and a variety of social science applications. A list of his published articles on his faculty webpage gives an idea of the variety of disciplines Dr. Gelman’s research covers. In addition, he has also published several books on statistics and political science.

“The things I used to put in long emails, I’ll blog.  Even if your blog only has five readers, that’s five times more people than would read an individual email.”

Dr. Andrew Gelman

His research interests also include education. His post “What’s the most important thing in statistics that’s not in the textbooks?” offers a statistics educator’s view of how statistics texts can help or hinder student learning, and a 2012 Ethics and Statistics article touches on similar ideas: the need for statistics educators to apply those heralded empirical practices to teaching and assessment. “Statistics is an ‘helper’ field in that we develop methods for others to use,” he explains. “In that sense, just about all my research is about education of one sort or another.”

Given his multidisciplinary interests, the backgrounds of his readers might be trickier to assume.

“I have no idea who my audience is!” he says, although he notes that post discussions sometimes help. “I have some sense of my commenters, but that’s about it.”

Nevertheless, having that blog readership can affect the platform he ultimately chooses for communicating some concepts and ideas. “The things I used to put in long emails, I’ll blog,” notes Dr. Gelman. “Even if your blog only has five readers, that’s five times more people than would read an individual email. And, in general, writing can be a good way to focus one’s thoughts.”

Statistical Modeling, Causal Inference, and Social Science:

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 For more ACI news and information, view the June 2, 2015 edition of the ACI InSights Newsletter.