"Five skills. Each one is counter-cyclical (becomes more valuable as hype recedes), resistant to LLM automation (requires human judgment that pattern-matching can’t replicate), and directly tied to the business outcomes executives actually pay for."
by Kaushik Rajan: https://towardsdatascience.com/the-ai-bubble-has-a-data-science-escape-hatch/

#DataScience #BayesianStatistics #BayesianStats #Bayesian #causalInference #experimentalDesign #SPC #statisticalProcessControl

#statstab #505 Beyond Confounders

Thoughts: What makes a good control and a bad control?

#counterfactuals #confounder #DAG #r #modelling #selectionbias #variance #control #causalinference

https://matheusfacure.github.io/python-causality-handbook/07-Beyond-Confounders.html

#statstab #497 On the Statistical Analysis of Experiments
With Manipulation Checks

Thoughts: All psychologists reading this title will panic. Yes, you can't just delete data and assume all is well.

#assumptions #QRPs #estimand #causalinference #ITT #ATE #bias

https://journals.sagepub.com/doi/pdf/10.1177/25152459241297537

"Mediators, confounders, colliders – a crash course in causal inference"
by Florian Hartig (2019): https://theoreticalecology.wordpress.com/2019/04/14/mediators-confounders-colliders-a-crash-course-in-causal-inference/

#offPolicy #causality #causalInference #stats #statistics #counterFactuals #probabilities #ML #ecology #confounding

#statstab #485 Bayesian ANCOVA and the ATE

Thoughts: Still grappling with the implications of using the causal inference approach to randomized experiments. But it's interesting.

#ATE #causalinference #ancova #ANOVA #rstats #estimand #counterfactuals

https://solomonkurz.netlify.app/blog/2025-07-20-within-person-factorial-experiments-log-normal-reaction-time-data/

#statstab #482 Introducing Causion: A web app for playing with DAGs

Thoughts: A very cool app. Let's you see exactly what your assumptions and DGP mean for your causal model.

#causal #causalinference #DAG #DAGs #dgp #tutorial #guide #education #pedagogy

https://pedermisager.org/blog/causion-dag-simulator/

Orthogonal Representation Learning for Estimating Causal Quantities

#CausalInference

https://arxiv.org/pdf/2502.04274

#statstab #474 {DeclareDesign} Observational : causal

Thoughts: If you want to do causal research with OS there is a lot more to consider than in #473

#design #research #rstats #education #tutorial #pedagogy #DiD #DAGs #causalinference

https://book.declaredesign.org/library/observational-causal.html

Surprising result, nice study design

When "Likes" went private on X there was no detectable change in the number of Likes received on posts by "high reputational risk" accounts

https://arxiv.org/pdf/2601.11140

#CausalInference #DifferenceInDifference #SocialMedia #Research