Summary of "Statistical Rethinking 2022 Lecture 01 - Golem of Prague"

The course aims to subjugate statistics to science, emphasizing the importance of integrating statistical modeling with scientific modeling and thinking.

Traditional introductory statistics courses focus on consulting flowcharts to pick procedures that yield p-values, which may not address fundamental causation adequately.
The course rethinks the role of statistics in research, aiming to fully integrate statistical and scientific modeling throughout a study.
The importance of Bayesian statistics is highlighted, as it is now considered mainstream in major scientific publications.
The metaphor of golems is used to represent powerful but potentially dangerous statistical models that require precise instructions to avoid misinterpretation.
The concept of owls is introduced to emphasize the importance of documenting work, understanding statistical and scientific models, and following a respectable scientific workflow.
Directed Acyclic Graphs (DAGs) are introduced as heuristic causal models that help clarify scientific thinking and guide the design of statistical procedures.
The course will cover topics such as causal inference, prediction, causal imputation, and the importance of understanding and representing causal relationships in statistical analysis.
The course structure includes a focus on theoretical s demand, scientific causal models, statistical procedures, validation through simulation, and analysis of real data.
The course encourages a deep understanding of statistical and scientific models, the importance of clear documentation, and the use of heuristic causal models like DAGs to guide statistical analysis.