decision science
Books
Seeing What Others Don’t Book Review: How Insight Becomes a Competitive Advantage
A strategic review of Seeing What Others Don’t by Gary Klein, exploring how insight is generated through perception, mental models, and multidisciplinary thinking. This article explains the three sources of insight and why better interpretation, not more data, creates a true competitive advantage in investing, analytics, and decision-making.
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News
Demagaga Week in Review February 20, 2026: Quantitative Thinking, Fitness Optimization, and Cyberpunk Culture
This week on Demagaga explores quantitative decision-making, fitness optimization tools, supplement reviews, and cyberpunk-inspired film and television analysis. From foundational data science books to macro tracking apps and energy drinks, alongside reviews of RoboCop, Fallout, and The Boys, this collection highlights the intersection of performance, analytics, and modern digital culture.
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Books
Risk Savvy Book Review: Why Simplicity Often Beats Complexity in Decision-Making
A practical review of Risk Savvy by Gerd Gigerenzer, explaining how risk literacy, simple heuristics, and clear communication improve decision-making. This article covers risk vs uncertainty, natural frequencies, and the limits of complex models in business, healthcare, and strategy.
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Books
Algorithms to Live By Book Review: Why Computer Science Might Be the Best Decision Framework You’re Not Using
A practical review of Algorithms to Live By by Brian Christian and Tom Griffiths, explaining how computer science principles improve real-world decision-making. This article covers optimal stopping, explore vs exploit, scheduling, and caching, showing how to allocate time, attention, and resources more effectively.
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Books
The Art of Statistics Book Review: Why Understanding Uncertainty Matters More Than Ever
A clear, practical review of The Art of Statistics by David Spiegelhalter, focused on interpreting data, understanding uncertainty, and communicating risk effectively. This article explains the data to model to inference pipeline and why context, variability, and framing are essential for better decisions in analytics, finance, and policy.
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Books
How Not to Be Wrong Book Review: Why Mathematical Thinking Is a Decision-Making Superpower
A clear, engaging review of How Not to Be Wrong by Jordan Ellenberg, explaining how mathematical thinking improves decision-making. This article covers regression to the mean, expected value, base rates, and statistical reasoning for professionals in analytics, finance, and strategy.
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Books
Technical Literacy and Modeling Intuition: The Quantitative MBA Reading Canon
Quantitative thinking only matters if it survives contact with real data. This Technical Literacy and Modeling Intuition canon brings together the essential books that teach how models behave, how data flows through systems, and how analytical insight is actually built, tested, and communicated. From statistical learning and forecasting to feature engineering, data infrastructure, and AI realism, these titles form the practical backbone every quantitatively minded MBA, analyst, and strategist needs to think clearly and build reliably in modern business.
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Books
The Book of Why Book Review: Why Causality Is the Missing Layer in Data Science
A clear, strategic review of The Book of Why by Judea Pearl and Dana Mackenzie, explaining why causality, not just correlation, is essential for better decision-making. This article breaks down the Ladder of Causation, causal diagrams, and counterfactual thinking for professionals in analytics, finance, and strategy.
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Books
Thinking in Bets Book Review: How to Make Better Decisions When Outcomes Lie
A sharp, practical review of Thinking in Bets by Annie Duke, focused on decision-making under uncertainty and the dangers of judging outcomes instead of process. This article explains resulting, probabilistic thinking, and how to improve judgment in business, finance, and analytics.
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Books
The Signal and the Noise Book Review: How to Think Clearly in a World of Data Overload
A sharp, practical review of The Signal and the Noise by Nate Silver, focused on probabilistic thinking, forecasting, and decision-making under uncertainty. This article explains signal vs noise, Bayesian reasoning, and why better judgment, not more data, leads to better predictions in finance, analytics, and strategy.
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