Modern science of making sense from greasy data
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“Drs. Murray and D’Agostino-Gowan provide the content that reflects the state of the art in the relatively recent interdisciplinary area of scientific methodology called causal inference. This would not be your first podcast on statistics; it has to be layered on top of a graduate degree in statistics, data science, epidemiology, public health, economics, quantitative social sciences, and the like. As I try to stay current and relevant in my own work (which is a different area of statistics), the podcast has been very helpful for me in getting a glimpse of the discipline where 90% of the current knowledge has been generated after I got my terminal degree (2005). Looking forward to new episodes, and keep doing great work!”
Grschunchibdseyv via Apple Podcasts ·
United States of America ·
06/05/24
More reviews of Casual Inference
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“Big fan of your podcast here north of the border.
Perhaps consider interviewing a clinician scientist, and if you already have my apologies for missing it!”
Markchung55 via Apple Podcasts ·
Canada ·
11/14/20
“This is a great podcast for people new to causal inference as well as those helping to advance the methods. It’s ‘casual’ and guests are buzzed if they introduce words or concepts that need definition. The hosts interview leaders in the field and the conversations are always fun and insightful....”Read full review »
JosephWesley via Apple Podcasts ·
United States of America ·
02/16/20
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“Love the podcast. It wonderful that references to articles are provided. That is so helpful.”
NotKG via Apple Podcasts ·
United States of America ·
12/18/19
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