# Causality

## Lectures on Causality: Jonas Peters, Part 2

## Lectures on Causality: Jonas Peters, Part 3

## Lectures on Causality: Jonas Peters, Part 4

## The Causal Foundations of Applied Probability and Statistics

DSA ADS Course - 2023

Probabilistic Logic, Probability Theory, Causality, Causal Inference, Applied Probability, Statistics

Discuss applied probability theory and causality.

The Causal Foundations of Applied Probability and Statistics - November, 2020

Abstract

## Data versus Science: Contesting the Soul of Data-Science

## The Seven Tools of Causal Inference, with Reflections on Machine Learning

DSA ADS Course - 2021

Causality, Causal Reasoning, Causal Inference, Machine Learning, Algorithms

Discuss causality and machine learning - contrast with statistical correlations.

The Seven Tools of Causal Inference, with Reflections on Machine Learning - March, 2019 By Judea Pearl

## Causally Colored Reflections on Leo Breiman’s “Statistical Modeling: The Two Cultures”

DSA ADS Course, 2022

Statistical Analysis, Data Interpretation, Causal Analysis, Causality, Data Fusion, Missing Data, Counterfactuals

Discuss Leo Breiman’s “Statistical Modeling: The Two Cultures” in light of recent advances in machine learning and causal inference and the separation between the data-fitting and data-interpretation components of statistical modeling.

July, 2021

## Statistical Modelling in the Age of Data Science

DSA ADS Course, 2022

Causal Machine learning, Double Machine Learning, Targeted Learning, Statistical Analysis, Data Interpretation, Causal Analysis, Causality, Data Fusion, Missing Data, Counterfactuals

Discuss recent advances in machine learning and causal inference and the separation between the data-fitting and data-interpretation components of statistical modeling.

Discuss causal machine learning, double machine learning and targeted learning.

Statistical Modelling in the Age of Data Science - July, 2021

Abstract

## Statistical Modeling The Two Cultures

DSA ADS Course, 2022

Statistical Analysis, Data Interpretation, Causal Analysis, Causality, Data Fusion, Missing Data, Counterfactuals

Discuss the two cultures of statistical modeling according to Leo Breiman in light of recent advances in machine learning and causal inference and the separation between the data-fitting and data-interpretation components of statistical modeling.