Extendability of Causal Graphical Models: Algorithms and Computational Complexity
On 21 Aug, 2021 By admin 0 Comments
External Course
The psychological roots of intellectual humility: The role of intelligence and cognitive flexibility
On 21 Aug, 2021 By admin 0 Comments
DSA ADS Course - 2021
Psychological roots of intellectual humility: The role of intelligence and cognitive flexibility
Human Decision Making, Intelligence, Cognitive Flexibility, Confirmation Bias, Intellectual Humility
Cognitive flexibility and having a diverse toolbox of conceptual frameworks is critical to high performance data science. Humility is important to admitting error and self correcting in near real-time situations.
Cognitive flexibility and humility is magic sauce to avoiding and mitigating confirmation bias and optimal decision-making.
Induction and Deduction in Bayesian Data Analysis
On 21 Aug, 2021 By admin 0 Comments
DSA ADS Course - 2021
Bayesian Data Analysis, Bayesian Decision Analysis
Abstract
Control of Confounding and Reporting of Results in Causal Inference Studies
On 21 Aug, 2021 By admin 0 Comments
An Introduction to Causal Inference
On 20 Aug, 2021 By admin 0 Comments
DSA ADS Course - 2021
Causal Inference, Directed Acyclic Graphs, Counterfactuals, D-separation, Do-calculus, Simpson’s Paradox, Structural Causal Model
Introduction to Causal Inference - Fabian Dablander
September, 2020
Abstract
Causal Inference and the Data-fusion Problem
On 20 Aug, 2021 By admin 0 Comments
DSA ADS Course - 2021
Causal Inference, Data-fusion, Causal Analysis, Causal Data Science, Counterfactuals, Selection Bias
Discuss concepts and techniques of different approaches to causal analysis, the curse of big data, data fusion and bias challenges. Discuss biases such as: confounding, sampling selection, and cross-population biases, along with a general, potential mitigation nonparametric framework for handling biases.
Discuss appropriate use of counterfactuals in causal analysis and risk of reasonable inference vs. unreasonable inference.
What is Causal Inference?
On 20 Aug, 2021 By admin 0 Comments
Counterfactual Data-Fusion for Online Reinforcement Learners
On 20 Aug, 2021 By admin 0 Comments
DSA ADS Course - 2021
Causal Reinforcement Learning, Counterfactuals, Counterfactual Data-Fusion, Online Reinforcement Learners
Discuss counterfactuals, risks of data fusion, causal reinforcement learning and fusion of observational and experimental data.
Counterfactual Data-Fusion for Online Reinforcement Learners - June, 2017
Abstract
A Critical View of the Structural Causal Model
On 16 Aug, 2021 By admin 0 Comments
DSA ADS Course - 2021
Causal Inference, Causality, Structural Causal Model, SCM
Discuss causality vs. correlation - causality vs. statistics in machine learning. Review techniques for attempting to find true causality.
In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. In the broadest sense correlation is any statistical association, though it commonly refers to the degree to which a pair of variables are linearly related.
Models Only Say What They’re Told to Say
On 13 Aug, 2021 By admin 0 Comments
July, 2021
Abstract
This short note is a reminder that all models only say what they are told to say. There can therefore be no discovery by models—discoveries go into models—and thus models should only be used in their predictive form, and only trusted when they have demonstrated independent success.
See also: Proper Use and Misuse of Modeling - DSA ADS Course 2022
DSA ADS Course - 2022