CAUSAL INFERENCE IN STATISTICS A Primer Causality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we

Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unifi

This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.

An accessible, contemporary introduction to the methods for determining cause and effect in the Social Sciences “Causation versus correlation has been the bas

David A. Freedman presents a definitive synthesis of his approach to statistical modeling and causal inference in the social sciences.