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Data, Inference, and Decisions
Data, Inference, and Decisions
Chapter 1: Binary Decision-Making
Binary Decision-Making and Error Rates
Hypothesis Testing and p-Values
Multiple Hypothesis Testing
Binary Classification
Decision Theory
Chapter 2: Bayesian modeling
Parameter Estimation and Bayesian Inference Fundamentals
Hierarchical Bayesian Models
Graphical Models
Bayesian Inference and Sampling
Chapter 3: Prediction
Chapter 4: Causal Inference
Understanding Association
Quantifying Association
Causality and Potential Outcomes
Causality in Randomized Experiments
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Generalized Linear Models
Generalized Linear Models
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This chapter will cover generalized linear models.