Symbolic Logic Protected: Basics of Statistical Causal Effects (3)Operating Variable Method and Summary
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2022-03
Symbolic Logic Symbolic Logic Protected: Basics of Statistical Causal Effects (2)Methods Using Regression Models and Matching and Stratified Analysis
Regression modeling methods for statistical causal inference utilized in digital transformation, artificial intelligence, and machine learning tasks; causal effect estimation using matching and stratified analysis methods
Symbolic Logic Protected: Basics of Statistical Causal Effects (1)Definition of Causal Effects Based on the Rubin Effect Model
Definition of causal effects and estimation of statistical causal effects (ATT, ATU, ATE) based on the Rubin effect model used for digital transformation, artificial intelligence and machine learning tasks
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Symbolic Logic Protected: Quasi-experimental design – how to derive causal relationships from observed data
How to verify causality for digital transformation, artificial intelligence , and machine learning tasks by first having the data for causal inference and then verifying causality from there.
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Symbolic Logic Protected: Correlation, Causation and Relational Structure (2) Backdoor Criteria
Actual backdoor criteria for narrowing down variables to observe intervention effects in causal inference for digital transformation , artificial intelligence, and machine learning tasks