Carnegie Mellon University

Instructional Videos

These videos show you how to use our tools and offer a deeper insight into causal discovery.

Gives an overview of the goals for the course and a basic working knowledge of graphical causal models.

 Explains modeling ideal interventions and their importance.

Explains interventions and causal graphs and how pre-intervention graphs will look in the post-intervention graph.

Using continuous variables and linear functions, this video explains structural equation models.

Explains the roadmap for the afternoon part of the course and the way in which you can specify models.

Looks at how to estimate the parameters of a model and how to do inference on those given models.

Explains how to load in real data, how to specify an hypothesis, and how to test the hypothesis.

Gives an overview of the material to be covered this morning and how to use bridge principles (Markov Axiom and D-separation).

Looks at model equivalence and explains the difference between Pattern and PAG representations.

Explains the theory of search and examines d-separation.

Gives an overview of the third day and in-depth look at what happens in a search for Patterns.

Contrasts multiple regression vs model search.

Discusses a variety of additional issues in causal modeling and discovery.

A 30-Minute Tutorial on Causal Modeling and Discovery

A Brief Introduction to Causal Network Discovery from Biomedical & Clinical Data

Overview of what Causal Discovery is, the purpose of causal discovery algorithms, an introduction to methods for discovering causal networks, and the available resources for discovering causal networks.

A 2-Hour Workshop on Causal Modeling and Discovery

Applying Computational Causal Discovery in Biomedicine

Other Tetrad Instructional Videos

Dataloader

How to use the dataloader in Tetrad.

Adding, Removing, and Reordering Data

How to use the different functions for your loaded data in Tetrad.

Transforming Data

How to transform your data into something more useful in Tetrad.