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1
Introduction
2
Causal model of weight
3
Categorical variables
4
Contrasts
5
Estimating a direct effect
6
Bayesian causal inference
7
Intermission
8
Curves from lines
9
Polynomial models
10
Splines
11
Summary
Description:
Explore advanced statistical concepts in this comprehensive lecture on categories, curves, and splines. Delve into causal models of weight, categorical variables, contrasts, and direct effect estimation. Gain insights into Bayesian causal inference and learn how to create curves from lines using polynomial models and splines. Follow along with detailed explanations and practical examples to enhance your understanding of these complex statistical techniques.

Statistical Rethinking 2022 - Categories, Curves & Splines

Richard McElreath
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