Rocco Di Tella
@roccoditella.bsky.social
Reposted by Rocco Di Tella
I'm teaching a grad seminar this winter on Prediction for Decision-making. We'll look at what it means to make good predictions for decision-making from various angles, with a focus on decisions for & about people.
Reading list: statmodeling.stat.columbia.edu/2024/12/06/n...
Suggestions welcome!
Reading list: statmodeling.stat.columbia.edu/2024/12/06/n...
Suggestions welcome!
New Course: Prediction for (Individualized) Decision-making | Statistical Modeling, Causal Inference, and Social Science
statmodeling.stat.columbia.edu
December 6, 2024 at 4:45 PM
I'm teaching a grad seminar this winter on Prediction for Decision-making. We'll look at what it means to make good predictions for decision-making from various angles, with a focus on decisions for & about people.
Reading list: statmodeling.stat.columbia.edu/2024/12/06/n...
Suggestions welcome!
Reading list: statmodeling.stat.columbia.edu/2024/12/06/n...
Suggestions welcome!
Reposted by Rocco Di Tella
Stop anthropomorphising LLM's, they don't like it.
November 30, 2024 at 9:56 AM
Stop anthropomorphising LLM's, they don't like it.
Reposted by Rocco Di Tella
Wait, are the AnthropicAI people seriously claiming to “unlock a rich theoretical landscape” for AI evaluation by proposing the use of…. error bars? And this secret trove of deep statistical insight starts with “use the Central Limit Theorem”?
Befuddling
Befuddling
November 27, 2024 at 10:09 PM
Wait, are the AnthropicAI people seriously claiming to “unlock a rich theoretical landscape” for AI evaluation by proposing the use of…. error bars? And this secret trove of deep statistical insight starts with “use the Central Limit Theorem”?
Befuddling
Befuddling
Reposted by Rocco Di Tella
Since it is inefficient to attempt to educate every reviewer individually, I am yeeting into your feed this clear paper from Gelman, Hill, and Yajima on how Bayesians can do even better than correcting for multiple comparisons. arxiv.org/abs/0907.2478
Why we (usually) don't have to worry about multiple comparisons
Applied researchers often find themselves making statistical inferences in settings that would seem to require multiple comparisons adjustments. We challenge the Type I error paradigm that underlies t...
arxiv.org
November 26, 2024 at 9:11 AM
Since it is inefficient to attempt to educate every reviewer individually, I am yeeting into your feed this clear paper from Gelman, Hill, and Yajima on how Bayesians can do even better than correcting for multiple comparisons. arxiv.org/abs/0907.2478
Reposted by Rocco Di Tella
Bought a book back in like, 2018, and it finally is relevant to some stuff I'm doing.
See kids? Books are great
See kids? Books are great
November 28, 2024 at 1:15 AM
Bought a book back in like, 2018, and it finally is relevant to some stuff I'm doing.
See kids? Books are great
See kids? Books are great