Books as Frameworks: Problem-Solving & Decision-Making
Table of Contents
Smart Choices (John S. Hammond et al.)
- Problem: How to define your decision problem to solve the right problem
- Objectives: How to clarify what you’re really trying to achieve with your decision
- Alternatives: How to make smarter choices by creating better alternatives to choose from
- Consequences: How to describe how well each alternative meets your objectives
- Tradeoffs: How to make tough compromises when you can’t achieve all your objectives at once
- Uncertainty: How to think about and act on uncertainties affecting your decision
- Risk Tolerance: How to account for your appetite for risk
- Linked Decisions: How to plan ahead by effectively coordinating current and future decisions
- Psychological Traps: How to avoid some of the tricks your mind can play on you when you’re deciding
- The Wise Decision Maker: How to make smart choices a way of life
The Art of Statistical Thinking (Albert Rutherford et al.)
Definition and Basic Concepts
- Sample Versus Population
- Descriptive Statistics
- Sample Statistics and Population Parameters
- Descriptive Statistics for Relative Position
- Data Visualization
- Comparing Alternative Distributions
- Normal Distribution
- Checking the Normality of a Distribution
- Concluding Remarks
Inferential Statistics
- Random (Repeated) Sampling and Sampling Distribution
- Understanding the Test Statistic
- Effect Size vs. Sample Size
- Inferential Statistics
- Concluding Remarks
Statistical Thinking
- Understanding Uncertainty
- Research Design
- Alpha, Beta, and Power
- Implications to Research with Big Data
- Choosing the Level of Significance
- A Brief History of Modern Statistics
- Concluding Remarks
How Is Statistics Applied in Real Life
- Investment Decision
- Opinion Polls
- Economics Research
- Medical Research
- Economic and Business Forecasting
- Stock Trading and Portfolio Selection
- Risk Management
- Concluding Remarks
Misinterpretations of Statistics
- Illusion of Statistical Significance
- Big Data Hubris: Misinterpretation of the Central Limit Theorem
- Sampling Bias
- Cherry-Picking
- Correlation, Not Causation
- Statistical Insignificance
- Misleading Visualization
The Field Guide to Understanding ‘Human Error’ (Sidney Dekker)
- Two Views of ‘Human Error’
- Containing Your Reactions to Failure
- Doing a ‘Human Error’ Investigation
- Explaining the Patterns of Breakdown
- Understanding Your Accident Model
- Creating an Effective Safety Department
- Building a Safety Culture
- Abandoning the Fallacy of a Quick Fix