Applied Probability
The Causal Foundations of Applied Probability and Statistics
DSA ADS Course - 2022
Probabilistic Logic, Probability Theory, Causality, Causal Inference, Applied Probability, Statistics
Discuss applied probability theory and causality.
The Causal Foundations of Applied Probability and Statistics - November, 2020
Abstract
The self-fulfilling prophecy of post-hoc power calculations
February, 2022
Abstract
Introduction to Probabilities, Graphs, and Causal Models
DSA ADS Course - 2022
Applied Probability, Causal Data Science, Causal Graphical Models
Discuss probability theory and practice using graphs and causal reasoning.
2013 - Introduction to Probabilities, Graphs, and Causal Models
Introduction to Graphical Models and Bayesian Networks
DSA ADS Course - 2022
Graphical Models, Bayesian Networks, Applied Probability, Probabilistic Causation, Causal Inference
Applied data scientists require high-level understanding of probability theory and specialized techniques to design systems and solve problems in the real world. Graphical model formalism provides a natural framework for the design of new data science systems.
Introduction to Probability
DSA ADS Course - 2022
Probability Theory, Applied Probability, Probabilistic Causation, Causal Inference
Understanding applied probability and accurate assessment of real-world risk is a critical part of high value data science.
Evolutionary Game Theory: Game Theory, Applied Probability, Scenario Planning
DSA ADS Course - 2021
Game Theory, Applied Probability, Scenario Planning, Evolutionary Game Theory
Important to have basic knowledge of game theory.
Game theory considers problems confronted by decision-makers with diverging interests like firms competing for a market. Players have to choose between strategies whose payoff depends on their rivals’ strategies. This interdependence leads to a mutual ‘outguessing’, as with chess (she thinks that I think that she thinks…).
Reasoning Under Uncertainty: Some Monte Carlo Results
DSA ADS Course - 2021
Applied Probability, Causal Data Science, Probabilistic Reasoning, Markov Chain Monte Carlo
Reasoning under Uncertainty: Some Monte Carlo Results - 1991
Abstract
The Sure Thing
DSA ADS Course - 2021
The Sure-Thing Principle, Causal Reasoning, Data-Driven Decision-Making, Algorithm Decision Making, Applied Probability, Nonlinear Utility Scale, Simpson’s Paradox, Blyth’s Game
Discuss applied probability, causal reasoning and types of decision making processes. Apply to both traditional algorithms and machine learning algorithms in decision making processes.
See also: The Sure-Thing Principle
The Sure Thing - 2021
Abstract
The Sure-Thing Principle
DSA ADS Course - 2021
The Sure-Thing Principle, Causal Reasoning, Data-Driven Decision-Making, Algorithm Decision Making, Applied Probability
Discuss applied probability, causal reasoning and types of decision making processes. Apply to both traditional algorithms and machine learning algorithms in decision making processes.
See also: The Sure Thing
The Sure-Thing Principle - 2016
Abstract