if you see hoof prints, think horses—not zebras

8 results back to index


pages: 147 words: 39,910

The Great Mental Models: General Thinking Concepts by Shane Parrish

Albert Einstein, anti-fragile, Atul Gawande, Barry Marshall: ulcers, bitcoin, Black Swan, colonial rule, correlation coefficient, correlation does not imply causation, cuban missile crisis, Daniel Kahneman / Amos Tversky, dark matter, delayed gratification, feminist movement, Garrett Hardin, if you see hoof prints, think horses—not zebras, index fund, Isaac Newton, Jane Jacobs, John Bogle, Linda problem, mandelbrot fractal, Pepsi Challenge, Philippa Foot, Pierre-Simon Laplace, Ponzi scheme, Richard Feynman, statistical model, stem cell, The Death and Life of Great American Cities, the map is not the territory, the scientific method, Thomas Bayes, Torches of Freedom, Tragedy of the Commons, trolley problem

We know that generally the flu is far more common than Ebola, so when a good doctor encounters a patient with what looks like the flu, the simplest explanation is almost certainly the correct one. A diagnosis of Ebola means a call to the Center for Disease Control and a quarantine—an expensive and panic-inducing mistake if the patient just has the flu. Thus, medical students are taught to heed the saying, “When you hear hoofbeats, think horses, not zebras.” And for patients, Occam’s Razor is a good counter to hypochondria. Based on the same principles, you factor in the current state of your health to an evaluation of your current symptoms. Knowing that the simplest explanation is most likely to be true can help us avoid unnecessary panic and stress.


pages: 292 words: 94,324

How Doctors Think by Jerome Groopman

affirmative action, Atul Gawande, classic study, Daniel Kahneman / Amos Tversky, deliberate practice, fear of failure, framing effect, if you see hoof prints, think horses—not zebras, index card, iterative process, lateral thinking, machine translation, medical malpractice, medical residency, Menlo Park, pattern recognition, placebo effect, seminal paper, stem cell, theory of mind

In medical school, and later during residency training, the emphasis is on learning the typical picture of a certain disorder, whether it is a peptic ulcer or a migraine or a kidney stone. Seemingly unusual or atypical presentations often get short shrift. "Common things are common" is another cliché that was drilled into me during my training. Another echoing maxim on rounds: "When you hear hoofbeats, think about horses, not zebras." Rachel Stein, trawling through the long list of causes of Pneumocystis pneumonia, found a zebra. A nutritional deficiency can cause impaired immune defense and provide fertile ground for this infection. With his characteristic élan, Pat Croskerry, at Dalhousie University in Halifax, has coined the phrase "zebra retreat" to describe a doctor's shying away from a rare diagnosis.

When you or your loved one asks simply, "What else could it be?" you help bring closer to the surface the reality of uncertainty in medicine. "What else could it be?" is a key safeguard against these errors in thinking: premature closure, framing effect, availability from recent experience, the bias that the hoofbeats are horses and not zebras. Each cognitive error constrains the pursuit of answers, and correcting the error helps the doctor think of a test or procedure that he didn't previously consider and can make the diagnosis. "Is there anything that doesn't fit?" may be your next question. This follow-up should further prompt the physician to pause and let his mind roam more broadly.


pages: 1,380 words: 190,710

Building Secure and Reliable Systems: Best Practices for Designing, Implementing, and Maintaining Systems by Heather Adkins, Betsy Beyer, Paul Blankinship, Ana Oprea, Piotr Lewandowski, Adam Stubblefield

air gap, anti-pattern, barriers to entry, bash_history, behavioural economics, business continuity plan, business logic, business process, Cass Sunstein, cloud computing, cognitive load, continuous integration, correlation does not imply causation, create, read, update, delete, cryptocurrency, cyber-physical system, database schema, Debian, defense in depth, DevOps, Edward Snowden, end-to-end encryption, exponential backoff, fault tolerance, fear of failure, general-purpose programming language, Google Chrome, if you see hoof prints, think horses—not zebras, information security, Internet of things, Kubernetes, load shedding, margin call, microservices, MITM: man-in-the-middle, NSO Group, nudge theory, operational security, performance metric, pull request, ransomware, reproducible builds, revision control, Richard Thaler, risk tolerance, self-driving car, single source of truth, Skype, slashdot, software as a service, source of truth, SQL injection, Stuxnet, the long tail, Turing test, undersea cable, uranium enrichment, Valgrind, web application, Y2K, zero day

Some of the advice that follows can help, but there’s no real substitute for understanding the system ahead of time (see Chapter 6). Distinguish horses from zebras When you hear hoofbeats, do you first think of horses, or zebras? Instructors sometime pose this question to medical students learning how to triage and diagnose diseases. It’s a reminder that most ailments are common—most hoofbeats are caused by horses, not zebras. You can imagine why this is helpful advice for a medical student: they don’t want to assume symptoms add up to a rare disease when, in fact, the condition is common and straightforward to remedy.


pages: 397 words: 109,631

Mindware: Tools for Smart Thinking by Richard E. Nisbett

affirmative action, Albert Einstein, availability heuristic, behavioural economics, big-box store, Cass Sunstein, choice architecture, cognitive dissonance, confounding variable, correlation coefficient, correlation does not imply causation, cosmological constant, Daniel Kahneman / Amos Tversky, dark matter, do well by doing good, Edward Jenner, endowment effect, experimental subject, feminist movement, fixed income, fundamental attribution error, Garrett Hardin, glass ceiling, Henri Poincaré, if you see hoof prints, think horses—not zebras, Intergovernmental Panel on Climate Change (IPCC), Isaac Newton, job satisfaction, Kickstarter, lake wobegon effect, libertarian paternalism, longitudinal study, loss aversion, low skilled workers, Menlo Park, meta-analysis, Neil Armstrong, quantitative easing, Richard Thaler, Ronald Reagan, selection bias, Shai Danziger, Socratic dialogue, Steve Jobs, Steven Levy, tacit knowledge, the scientific method, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, Tragedy of the Commons, William of Occam, Yitang Zhang, Zipcar

Probably much more important than the rather minimal formal training in statistics, students learn about medical conditions and human behavior in potentially quantifiable ways and reason about them in explicitly statistical terms. “The patient has symptoms A, B, and C and does not have D and E. What is the likelihood that the patient has Disease Y? Disease Z? Disease Z, you say? You’re probably wrong about that. Disease Z is quite rare. If you hear hoofbeats, think horses, not zebras. What tests would you want to order? Tests Q and R, you say? You’re wrong. Those tests are not very statistically reliable; moreover they’re quite expensive. You might order test M or N, which are cheap and statistically reliable, but neither is a very valid predictor of either disease Y or disease Z.”


pages: 283 words: 81,376

The Doomsday Calculation: How an Equation That Predicts the Future Is Transforming Everything We Know About Life and the Universe by William Poundstone

Albert Einstein, anthropic principle, Any sufficiently advanced technology is indistinguishable from magic, Arthur Eddington, Bayesian statistics, behavioural economics, Benoit Mandelbrot, Berlin Wall, bitcoin, Black Swan, conceptual framework, cosmic microwave background, cosmological constant, cosmological principle, CRISPR, cuban missile crisis, dark matter, DeepMind, digital map, discounted cash flows, Donald Trump, Doomsday Clock, double helix, Dr. Strangelove, Eddington experiment, Elon Musk, Geoffrey Hinton, Gerolamo Cardano, Hans Moravec, heat death of the universe, Higgs boson, if you see hoof prints, think horses—not zebras, index fund, Isaac Newton, Jaron Lanier, Jeff Bezos, John Markoff, John von Neumann, Large Hadron Collider, mandelbrot fractal, Mark Zuckerberg, Mars Rover, Neil Armstrong, Nick Bostrom, OpenAI, paperclip maximiser, Peter Thiel, Pierre-Simon Laplace, Plato's cave, probability theory / Blaise Pascal / Pierre de Fermat, RAND corporation, random walk, Richard Feynman, ride hailing / ride sharing, Rodney Brooks, Ronald Reagan, Ronald Reagan: Tear down this wall, Sam Altman, Schrödinger's Cat, Search for Extraterrestrial Intelligence, self-driving car, Silicon Valley, Skype, Stanislav Petrov, Stephen Hawking, strong AI, tech billionaire, Thomas Bayes, Thomas Malthus, time value of money, Turing test

Doyle joins Bayes in making the subversive point that the lack of evidence (a dog not barking) can be as revealing as affirmative evidence is. Bayes’s rule says to look at the ratio of probabilities. The dog not barking is probable with a familiar visitor but improbable with a stranger. That is reason to favor the first possibility. 3. “When you hear hoofbeats look for horses, not zebras.” All else being equal, the more common explanation is to be preferred. Here’s another example: In the third grade I won a trophy for kickball. Which was more likely? • I won the trophy because I was the best at kickball out of all the kids in the third grade. • I won because it was a participation trophy (handed out to every kid to boost self-esteem).


pages: 277 words: 88,539

Singular Intimacies: Becoming a Doctor at Bellevue by Danielle Ofri

if you see hoof prints, think horses—not zebras, index card, medical residency, placebo effect, rent stabilization, union organizing

Perhaps I was biased, but young people who looked like concentration camp victims in New York City in the early 1990s usually had AIDS. Unless she had a rare genetic syndrome or some exotic tropical disease. But it was the attendings who always admonished the medical students—“When you hear hoofbeats, look for horses, not zebras.” Eileen stabilized in the ICU and was transferred back to my team a few days later. I learned from her family that Eileen had been sick for at least a few months, and that despite her mother’s pleadings, would not see a doctor. She had grown so weak that she could no longer get up from the living room couch.


Super Thinking: The Big Book of Mental Models by Gabriel Weinberg, Lauren McCann

Abraham Maslow, Abraham Wald, affirmative action, Affordable Care Act / Obamacare, Airbnb, Albert Einstein, anti-pattern, Anton Chekhov, Apollo 13, Apple Newton, autonomous vehicles, bank run, barriers to entry, Bayesian statistics, Bernie Madoff, Bernie Sanders, Black Swan, Broken windows theory, business process, butterfly effect, Cal Newport, Clayton Christensen, cognitive dissonance, commoditize, correlation does not imply causation, crowdsourcing, Daniel Kahneman / Amos Tversky, dark pattern, David Attenborough, delayed gratification, deliberate practice, discounted cash flows, disruptive innovation, Donald Trump, Douglas Hofstadter, Dunning–Kruger effect, Edward Lorenz: Chaos theory, Edward Snowden, effective altruism, Elon Musk, en.wikipedia.org, experimental subject, fake news, fear of failure, feminist movement, Filter Bubble, framing effect, friendly fire, fundamental attribution error, Goodhart's law, Gödel, Escher, Bach, heat death of the universe, hindsight bias, housing crisis, if you see hoof prints, think horses—not zebras, Ignaz Semmelweis: hand washing, illegal immigration, imposter syndrome, incognito mode, income inequality, information asymmetry, Isaac Newton, Jeff Bezos, John Nash: game theory, karōshi / gwarosa / guolaosi, lateral thinking, loss aversion, Louis Pasteur, LuLaRoe, Lyft, mail merge, Mark Zuckerberg, meta-analysis, Metcalfe’s law, Milgram experiment, minimum viable product, moral hazard, mutually assured destruction, Nash equilibrium, Network effects, nocebo, nuclear winter, offshore financial centre, p-value, Paradox of Choice, Parkinson's law, Paul Graham, peak oil, Peter Thiel, phenotype, Pierre-Simon Laplace, placebo effect, Potemkin village, power law, precautionary principle, prediction markets, premature optimization, price anchoring, principal–agent problem, publication bias, recommendation engine, remote working, replication crisis, Richard Feynman, Richard Feynman: Challenger O-ring, Richard Thaler, ride hailing / ride sharing, Robert Metcalfe, Ronald Coase, Ronald Reagan, Salesforce, school choice, Schrödinger's Cat, selection bias, Shai Danziger, side project, Silicon Valley, Silicon Valley startup, speech recognition, statistical model, Steve Jobs, Steve Wozniak, Steven Pinker, Streisand effect, sunk-cost fallacy, survivorship bias, systems thinking, The future is already here, The last Blockbuster video rental store is in Bend, Oregon, The Present Situation in Quantum Mechanics, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Tragedy of the Commons, transaction costs, uber lyft, ultimatum game, uranium enrichment, urban planning, vertical integration, Vilfredo Pareto, warehouse robotics, WarGames: Global Thermonuclear War, When a measure becomes a target, wikimedia commons

The Greco-Roman astronomer Ptolemy (circa A.D. 90–168) stated, “We consider it a good principle to explain the phenomena by the simplest hypotheses possible.” More recently, the composer Roger Sessions, paraphrasing Albert Einstein, put it like this: “Everything should be made as simple as it can be, but not simpler!” In medicine, it’s known by this saying: “When you hear hoofbeats, think of horses, not zebras.” A practical tactic is to look at your explanation of a situation, break it down into its constituent assumptions, and for each one, ask yourself: Does this assumption really need to be here? What evidence do I have that it should remain? Is it a false dependency? For example, Ockham’s razor would be helpful in the search for a long-term romantic partner.


pages: 321 words: 92,828

pages: 506 words: 132,373

pages: 685 words: 203,949

The Organized Mind: Thinking Straight in the Age of Information Overload by Daniel J. Levitin

Abraham Maslow, airport security, Albert Einstein, Amazon Mechanical Turk, Anton Chekhov, autism spectrum disorder, Bayesian statistics, behavioural economics, big-box store, business process, call centre, Claude Shannon: information theory, cloud computing, cognitive bias, cognitive load, complexity theory, computer vision, conceptual framework, correlation does not imply causation, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, data science, deep learning, delayed gratification, Donald Trump, en.wikipedia.org, epigenetics, Eratosthenes, Exxon Valdez, framing effect, friendly fire, fundamental attribution error, Golden Gate Park, Google Glasses, GPS: selective availability, haute cuisine, How many piano tuners are there in Chicago?, human-factors engineering, if you see hoof prints, think horses—not zebras, impulse control, index card, indoor plumbing, information retrieval, information security, invention of writing, iterative process, jimmy wales, job satisfaction, Kickstarter, language acquisition, Lewis Mumford, life extension, longitudinal study, meta-analysis, more computing power than Apollo, Network effects, new economy, Nicholas Carr, optical character recognition, Pareto efficiency, pattern recognition, phenotype, placebo effect, pre–internet, profit motive, randomized controlled trial, Rubik’s Cube, Salesforce, shared worldview, Sheryl Sandberg, Skype, Snapchat, social intelligence, statistical model, Steve Jobs, supply-chain management, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Thomas Bayes, traumatic brain injury, Turing test, Twitter Arab Spring, ultimatum game, Wayback Machine, zero-sum game

The base rate for doctors is higher, and so if you know nothing at all about the party, your best guess is you’ll run into more doctors than cabinet members. Similarly, if you suddenly get a headache and you’re a worrier, you may fear that you have a brain tumor. Unexplained headaches are very common; brain tumors are not. The cliché in medical diagnostics is “When you hear hoofbeats, think horses, not zebras.” In other words, don’t ignore the base rate of what is most likely, given the symptoms. Cognitive psychology experiments have amply demonstrated that we typically ignore base rates in making judgments and decisions. Instead, we favor information we think is diagnostic, to use a medical term.


pages: 509 words: 92,141

The Pragmatic Programmer by Andrew Hunt, Dave Thomas

A Pattern Language, Broken windows theory, business logic, business process, buy low sell high, c2.com, combinatorial explosion, continuous integration, database schema, domain-specific language, don't repeat yourself, Donald Knuth, Ford Model T, Free Software Foundation, general-purpose programming language, George Santayana, Grace Hopper, higher-order functions, if you see hoof prints, think horses—not zebras, index card, Kaizen: continuous improvement, lateral thinking, loose coupling, Menlo Park, MVC pattern, off-by-one error, premature optimization, Ralph Waldo Emerson, revision control, Schrödinger's Cat, slashdot, sorting algorithm, speech recognition, systems thinking, the Cathedral and the Bazaar, traveling salesman, urban decay, Y2K

When finally forced to sit down and read the documentation on select, he discovered the problem and corrected it in a matter of minutes. We now use the phrase "select is broken" as a gentle reminder whenever one of us starts blaming the system for a fault that is likely to be our own. Tip 26 "select" Isn't Broken Remember, if you see hoof prints, think horses—not zebras. The OS is probably not broken. And the database is probably just fine. If you "changed only one thing" and the system stopped working, that one thing was likely to be responsible, directly or indirectly, no matter how farfetched it seems. Sometimes the thing that changed is outside of your control: new versions of the OS, compiler, database, or other third-party software can wreak havoc with previously correct code.



pages: 719 words: 181,090

Site Reliability Engineering: How Google Runs Production Systems by Betsy Beyer, Chris Jones, Jennifer Petoff, Niall Richard Murphy

"Margaret Hamilton" Apollo, Abraham Maslow, Air France Flight 447, anti-pattern, barriers to entry, business intelligence, business logic, business process, Checklist Manifesto, cloud computing, cognitive load, combinatorial explosion, continuous integration, correlation does not imply causation, crowdsourcing, database schema, defense in depth, DevOps, en.wikipedia.org, exponential backoff, fail fast, fault tolerance, Flash crash, George Santayana, Google Chrome, Google Earth, if you see hoof prints, think horses—not zebras, information asymmetry, job automation, job satisfaction, Kubernetes, linear programming, load shedding, loose coupling, machine readable, meta-analysis, microservices, minimum viable product, MVC pattern, no silver bullet, OSI model, performance metric, platform as a service, proprietary trading, reproducible builds, revision control, risk tolerance, side project, six sigma, the long tail, the scientific method, Toyota Production System, trickle-down economics, warehouse automation, web application, zero day

Fixing the first and second common pitfalls is a matter of learning the system in question and becoming experienced with the common patterns used in distributed systems. The third trap is a set of logical fallacies that can be avoided by remembering that not all failures are equally probable—as doctors are taught, “when you hear hoofbeats, think of horses not zebras.”4 Also remember that, all things being equal, we should prefer simpler explanations.5 Finally, we should remember that correlation is not causation:6 some correlated events, say packet loss within a cluster and failed hard drives in the cluster, share common causes—in this case, a power outage, though network failure clearly doesn’t cause the hard drive failures nor vice versa.


The Autistic Brain: Thinking Across the Spectrum by Temple Grandin, Richard Panek

Apollo 11, Asperger Syndrome, autism spectrum disorder, correlation does not imply causation, dark matter, David Brooks, deliberate practice, double helix, ghettoisation, Gregor Mendel, if you see hoof prints, think horses—not zebras, impulse control, Khan Academy, Mark Zuckerberg, meta-analysis, mouse model, neurotypical, pattern recognition, phenotype, Richard Feynman, selective serotonin reuptake inhibitor (SSRI), Silicon Valley, Steve Jobs, The future is already here, theory of mind, traumatic brain injury, twin studies

Oral stereotypies are common in all grazing animals, because that’s what they do all day. They graze. Other ARBs—rocking, repetitive jumping, and so on, or “non-locomotory body movements.” The zoo animals I call the “big pretty animals”—the big predators such as the lions, tigers, and bears—pace. Ungulates, which are the hoofed animals—horses, cows, rhinoceroses, pigs, zebras, llamas—do stereotypies with their mouths. Most of the other animals, including primates and lab rats, develop movement stereotypies in the third category. In human disorders such as autism, the abnormal behavior is usually in the first or third category. One of the most extreme cases of stereotypy I’ve ever seen was in a female wolf I saw at a wolf shelter.


pages: 364 words: 112,681

Moneyland: Why Thieves and Crooks Now Rule the World and How to Take It Back by Oliver Bullough

Alan Greenspan, banking crisis, Bernie Madoff, bitcoin, blood diamond, Bretton Woods, Brexit referendum, BRICs, British Empire, capital controls, central bank independence, corporate governance, cryptocurrency, cuban missile crisis, dark matter, diversification, Donald Trump, energy security, failed state, financial engineering, Flash crash, Francis Fukuyama: the end of history, full employment, Global Witness, high net worth, if you see hoof prints, think horses—not zebras, income inequality, joint-stock company, land bank, liberal capitalism, liberal world order, mass immigration, medical malpractice, Navinder Sarao, offshore financial centre, plutocrats, Plutonomy: Buying Luxury, Explaining Global Imbalances, rent-seeking, Richard Feynman, risk tolerance, Sloane Ranger, sovereign wealth fund, Suez crisis 1956, WikiLeaks

And why, as Cole had asked him when that first ambulance attended his house, if he had such a quintessentially English name, did he sound so very Russian? But these were tiny details only picked up later. Any doctor will tell you that the guiding mantra for dealing with newly arrived patients is that common things are common. If you see hoof prints, think horses, not zebras; if you see an otherwise healthy man vomiting and suffering from diarrhoea, think gastroenteritis, not assassination ordered at the highest levels of a foreign government. The next morning, Carter was started on ciprofloxacin, an antibiotic that would combat any nasty bugs that were upsetting his stomach.


pages: 504 words: 147,722

Doing Harm: The Truth About How Bad Medicine and Lazy Science Leave Women Dismissed, Misdiagnosed, and Sick by Maya Dusenbery

Affordable Care Act / Obamacare, Atul Gawande, autism spectrum disorder, equal pay for equal work, feminist movement, gender pay gap, Helicobacter pylori, if you see hoof prints, think horses—not zebras, Joan Didion, longitudinal study, meta-analysis, microaggression, obamacare, opioid epidemic / opioid crisis, phenotype, pre–internet, RAND corporation, randomized controlled trial, selection bias, selective serotonin reuptake inhibitor (SSRI), sexual politics, Skype, stem cell, TED Talk, women in the workforce

On average, it takes them over seven years to be correctly diagnosed. Along the way, these patients visit four primary care doctors and four specialists and receive two to three misdiagnoses. That it takes longer to be diagnosed with a rare disease than a more common one is not surprising. Doctors are taught that when they hear hoofbeats, they should think of horses, not zebras, and it may take some time to rule out more likely conditions and realize that they may, in fact, be looking at a zebra. But this staggering seven-year delay is decidedly not simply because it takes that long for doctors to crack a challenging case. According to a survey of 12,000 patients with several rare diseases in Europe, published by Eurordis in 2009, those who were initially misdiagnosed experienced longer diagnostic journeys.


pages: 492 words: 149,259

Big Bang by Simon Singh

Albert Einstein, Albert Michelson, All science is either physics or stamp collecting, Andrew Wiles, anthropic principle, Arthur Eddington, Astronomia nova, Bletchley Park, Boeing 747, Brownian motion, carbon-based life, Cepheid variable, Chance favours the prepared mind, Charles Babbage, Commentariolus, Copley Medal, cosmic abundance, cosmic microwave background, cosmological constant, cosmological principle, dark matter, Dava Sobel, Defenestration of Prague, discovery of penicillin, Dmitri Mendeleev, Eddington experiment, Edmond Halley, Edward Charles Pickering, Eratosthenes, Ernest Rutherford, Erwin Freundlich, Fellow of the Royal Society, Ford Model T, fudge factor, Hans Lippershey, Harlow Shapley and Heber Curtis, Harvard Computers: women astronomers, heat death of the universe, Henri Poincaré, horn antenna, if you see hoof prints, think horses—not zebras, Index librorum prohibitorum, information security, invention of the telescope, Isaac Newton, Johannes Kepler, John von Neumann, Karl Jansky, Kickstarter, Louis Daguerre, Louis Pasteur, luminiferous ether, Magellanic Cloud, Murray Gell-Mann, music of the spheres, Olbers’ paradox, On the Revolutions of the Heavenly Spheres, Paul Erdős, retrograde motion, Richard Feynman, scientific mainstream, Simon Singh, Stephen Hawking, Strategic Defense Initiative, the scientific method, Thomas Kuhn: the structure of scientific revolutions, time dilation, unbiased observer, Wilhelm Olbers, William of Occam

Applying Occam’s razor, you decide that the storm, rather than the twin meteorites, is the more likely explanation because it is the simpler one. Occam’s razor does not guarantee the right answer, but it does usually point us towards the correct one. Doctors often rely on Occam’s razor when diagnosing an illness, and medical students are advised: ‘When you hear hoof beats, think horses, not zebras.’ On the other hand, conspiracy theorists despise Occam’s razor, often rejecting a simple explanation in favour of a more convoluted and intriguing line of reasoning. Occam’s razor favoured the Copernican model (one circle per planet) over the Ptolemaic model (one epicycle, deferent, equant and eccentric per planet), but Occam’s razor is only decisive if two theories are equally successful, and in the sixteenth century the Ptolemaic model was clearly stronger in several ways; most notably, it made more accurate predictions of planetary positions.


pages: 533 words: 125,495

Rationality: What It Is, Why It Seems Scarce, Why It Matters by Steven Pinker

affirmative action, Albert Einstein, autonomous vehicles, availability heuristic, Ayatollah Khomeini, backpropagation, basic income, behavioural economics, belling the cat, Black Lives Matter, butterfly effect, carbon tax, Cass Sunstein, choice architecture, classic study, clean water, Comet Ping Pong, coronavirus, correlation coefficient, correlation does not imply causation, COVID-19, critical race theory, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, data science, David Attenborough, deep learning, defund the police, delayed gratification, disinformation, Donald Trump, Dr. Strangelove, Easter island, effective altruism, en.wikipedia.org, Erdős number, Estimating the Reproducibility of Psychological Science, fake news, feminist movement, framing effect, George Akerlof, George Floyd, germ theory of disease, high batting average, if you see hoof prints, think horses—not zebras, index card, Jeff Bezos, job automation, John Nash: game theory, John von Neumann, libertarian paternalism, Linda problem, longitudinal study, loss aversion, Mahatma Gandhi, meta-analysis, microaggression, Monty Hall problem, Nash equilibrium, New Journalism, Paul Erdős, Paul Samuelson, Peter Singer: altruism, Pierre-Simon Laplace, placebo effect, post-truth, power law, QAnon, QWERTY keyboard, Ralph Waldo Emerson, randomized controlled trial, replication crisis, Richard Thaler, scientific worldview, selection bias, social discount rate, social distancing, Social Justice Warrior, Stanford marshmallow experiment, Steve Bannon, Steven Pinker, sunk-cost fallacy, TED Talk, the scientific method, Thomas Bayes, Tragedy of the Commons, trolley problem, twin studies, universal basic income, Upton Sinclair, urban planning, Walter Mischel, yellow journalism, zero-sum game

And translated into common sense, it works like this. Now that you’ve seen the evidence, how much should you believe the idea? First, believe it more if the idea was well supported, credible, or plausible to start with—if it has a high prior, the first term in the numerator. As they say to medical students, if you hear hoofbeats outside the window, it’s probably a horse, not a zebra. If you see a patient with muscle aches, he’s more likely to have the flu than kuru (a rare disease seen among the Fore tribe in New Guinea), even if the symptoms are consistent with both diseases. Second, believe the idea more if the evidence is especially likely to occur when the idea is true—namely if it has a high likelihood, the second term in the numerator.


pages: 208 words: 67,288

pages: 1,758 words: 342,766

Code Complete (Developer Best Practices) by Steve McConnell

Ada Lovelace, Albert Einstein, Buckminster Fuller, business logic, call centre, classic study, continuous integration, data acquisition, database schema, don't repeat yourself, Donald Knuth, fault tolerance, General Magic , global macro, Grace Hopper, haute cuisine, if you see hoof prints, think horses—not zebras, index card, inventory management, iterative process, Larry Wall, loose coupling, Menlo Park, no silver bullet, off-by-one error, Perl 6, place-making, premature optimization, revision control, Sapir-Whorf hypothesis, seminal paper, slashdot, sorting algorithm, SQL injection, statistical model, Tacoma Narrows Bridge, the Cathedral and the Bazaar, the scientific method, Thomas Kuhn: the structure of scientific revolutions, Turing machine, web application

A pair of studies performed many years ago found that, of total errors reported, roughly 95% are caused by programmers, 2% by systems software (the compiler and the operating system), 2% by some other software, and 1% by the hardware (Brown and Sampson 1973, Ostrand and Weyuker 1984). Systems software and development tools are used by many more people today than they were in the 1970s and 1980s, and so my best guess is that, today, an even higher percentage of errors are the programmers' fault. If you see hoof prints, think horses—not zebras. The OS is probably not broken. And the database is probably just fine. — Andy Hunt Dave Thomas Clerical errors (typos) are a surprisingly common source of problems. One study found that 36% of all construction errors were clerical mistakes (Weiss 1975). A 1987 study of almost 3 million lines of flight-dynamics software found that 18% of all errors were clerical (Card 1987).


The Greatest Show on Earth: The Evidence for Evolution by Richard Dawkins

Alfred Russel Wallace, Andrew Wiles, Arthur Eddington, back-to-the-land, Claude Shannon: information theory, correlation does not imply causation, Craig Reynolds: boids flock, Danny Hillis, David Attenborough, discovery of DNA, Dmitri Mendeleev, domesticated silver fox, double helix, en.wikipedia.org, epigenetics, experimental subject, Gregor Mendel, heat death of the universe, if you see hoof prints, think horses—not zebras, invisible hand, Large Hadron Collider, Louis Pasteur, out of africa, phenotype, precautionary principle, Thomas Malthus

Similarly, impalas and gnus* are close cousins of each other, and slightly more distant cousins of giraffes and okapis. All four of them are more distant cousins still of other cloven-hoofed animals, such as pigs and warthogs (which are cousins of each other and of peccaries). All the cloven-hoofed animals are more distant cousins of horses and zebras (which don’t have cloven hooves and are close cousins of each other). We can go on as long as we like, bracketing pairs of cousins into groups, and groups of groups of cousins, and (groups of (groups of (groups of cousins))). I have slipped into using brackets automatically, and you know just what they signify.


pages: 561 words: 167,631