```{r setup, include=FALSE} options(repos = c(CRAN = "https://cran.rstudio.com/")) knitr::opts_chunk$set(message = FALSE) ``` # Syllabus {.unnumbered} ```{=html}

The complete module-and-topic map of the book. Click any module to open its overview, or jump straight to a topic within a chapter.

Four-Module Path ยท 24 Topics
IIntroduction to Decision Science4 topics
Foundations of Decision Making
1Overview of the Decision-Making Process 2Rationality and Decision Theory 3Types of Decisions and Decision Problems 4Decision Trees and Probability Theory
IIDecision Analysis and Data Uncertainty7 topics
Structuring and Evaluating Decisions
5Structuring Decision Problems 6Decision Criteria and Utility Theory 7Multi-Criteria Decision Analysis (MCDA) 8Sensitivity Analysis and Risk Assessment
Uncertainty, Probability and Simulation
9Sources of Uncertainty and Risk 10Probability Distributions and Statistical Inference 11Monte Carlo Simulation and Bootstrapping
IIIDecision-making Frameworks and Behavioral Decision Making6 topics
Quantitative and Strategic Frameworks
12Cost-Benefit Analysis and Net Present Value 13Decision-making under Risk and Uncertainty 14Game Theory and Strategic Decision Making
Behavioural Decision Making
15Cognitive Biases and Heuristics 16Prospect Theory and Loss Aversion 17Framing and its Effect on Decision Making
IVData Analytics, Decision Making, and Ethics6 topics
Analytics and Predictive Modelling
18Introduction to Data Analytics and Machine Learning 19Regression Analysis and Predictive Modeling 20Decision Trees and Random Forests
Ethics and Responsibility
21Ethical Considerations in Decision Making 22Decision Making and Social Responsibility 23Sustainability and Decision Making
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