Studying Mental Models

Intro:

Several years ago, I went down the rabbit hole of studying Warren Buffet and Charlie Munger and fell in love with the way they approached acquiring knowledge and perfecting their craft. I was searching for more material on their philosophy and struck gold when I discovered Shane Parrish's Farnham Street. I am extremely grateful for what Shane has put together and continue to learn from his writing every day.

One of the major topics that he covers is Charlie Munger's concept of developing a latticework of mental models in order to gain worldly wisdom. Shane summarizes this concept nicely on his blog:

Acquiring knowledge may seem like a daunting task. There is so much to know and time is precious. Luckily, we don’t have to master everything. To get the biggest bang for our buck we can study the big ideas from the big disciplines: physics, biology, psychology, philosophy, literature, sociology, history, and a few others. We call these big ideas mental models. Our aim is not to remember facts and try to repeat them when asked, the way you studied for your high school history exams. We’re going to try and hang these ideas on a latticework of mental models, with vivid examples in our head to help us remember and apply them. The latticework of mental models puts them in a useable form to analyze a wide variety of situations and enables us to make better decisions. And when big ideas from multiple disciplines all point towards the same conclusion, we can begin to conclude that we’ve hit on an important truth.

Shane has accumulated a wonderful list of mental models that everyone should take the time to study and understand. He has put together blog posts on several of the topics but hasn't had a chance to get to all of them yet. Building on his work, I wanted to put together a way to study and memorize these models. In order to do that, I combined a few techniques that I have collected from people much smarter than I am.

The first is using the Feynman Technique to understand the difference between knowing something and knowing the name of something. Richard Feynman suggests a simple process when learning a new concept:

1. Choose a Concept
2. Teach it to a Toddler
3. Identify Gaps and Go Back to The Source Material
4. Review and Simplify

This forces you to have a deep understanding of the concept and to be able to explain it in simple language. You can't rely on technical terminology to communicate the concept.

The second technique that I am using is spaced repetition that I discovered on Derek Sivers' blog. As Sivers explains:

Say if you learn a new word in a foreign language, you'd want to practice it again a few minutes after hearing it, then a few hours, then the next day, then in 2 days, then 5 days, then 10 days, 3 weeks, 6 weeks, 3 months, 8 months, etc. After a while it's basically permanently memorized with a rare reminder.

There is spaced repetition software that you can use in order to manage the intervals that you are exposed to the concepts based on your feedback. One great tool for this is the AnkiApp. A great feature of this tool is that it allows you to import sets of flashcards from Quizlet. I am in the process of adding all of the mental models below into Quizlet so that anyone can import them into AnkiApp and follow this process. I will link to each set below when I am finished. (see Mental Models)

One important thing to remember is that the goal is not to remember the technical definition that I have added below. The goal is to use that as a trigger and a reminder of the concept. I have added a note to each card to explain the model in your own words and to provide an example. If you aren't able to do that, then follow the links below and do a refresher on the model until you know it well enough to explain it to a toddler.

Please let me know if you spot any errors or have any feedback on how I can improve this process. Thanks!

Mental Models:

Tools:

• Quizlet
• AnkiApp

Mental Model Flashcards:

• All Flashcards
• Psychology
• Business
• Investing
• Ecology
• Economics
• Engineering
• Mathematics
• Statistics
• Chemistry
• Physics
• Biology
• More Models

Psychology (misjudgments)

Biases emanating from the Availability Heuristic:

• Ease of Recall:  (Farnam / Wikipedia) suggests that if something is more easily recalled in memory it must occur with a higher probability.
• Retrievability: (Farnam / Wikipedia) suggests that we are biased in assessments of frequency in part because of our memory structure limitations and our search mechanisms. It’s the way we remember that matters.

Biases emanating from the Representativeness Heuristic

• Bias from insensitivity to base rates: (Farnam / Wikipedia) also called base rate neglect or base rate bias. If presented with related base rate information (i.e. generic, general information) and specific information (information only pertaining to a certain case), the mind tends to ignore the former and focus on the latter.
• Bias from insensitivity to sample size: (Farnam / Wikipedia) a cognitive bias that occurs when people judge the probability of obtaining a sample statistic without respect to the sample size. For example, in one study subjects assigned the same probability to the likelihood of obtaining a mean height of above six feet [183 cm] in samples of 10, 100, and 1,000 men. In other words, variation is more likely in smaller samples, but people may not expect this.
• Misconceptions of chance: (Farnam / Wikipedia) We tend to believe that the probability of an independent event is lowered when it has happened recently or that the probability is increased when it hasn’t happened recently.
• Regression to the mean: (Farnam / Wikipedia) the phenomenon that if a variable is extreme on its first measurement, it will tend to be closer to the average on its second measurement—and if it is extreme on its second measurement, it will tend to have been closer to the average on its first.
• Bias from conjunction fallacy: (Farnam / Wikipedia) which people commit when they judge a conjunction or two events to be more probable than one of the events in a direct comparison.

Biases emanating from the Confirmation Heuristic

• Confirmation bias: (Farnam / Wikipedia) the tendency to seek information that confirms prior conclusions and to ignore evidence to the contrary.
• Bias from anchoring: (Farnam / Wikipedia) the common human tendency to rely too heavily on the first piece of information offered (the "anchor") when making decisions.
• Conjunctive and disjunctive-events bias: (Farnam / Wikipedia) occurs when it is assumed that specific conditions are more probable than a single general one. According to Daniel Kahneman and his long-time co-author Amos Tversky (1974): “A complex system, such as a nuclear reactor or the human body, will malfunction if any of its essential components fails.” They continue, “Even when the likelihood of failure in each component is slight, the probability of an overall failure can be high if many components are involved.”
• Bias from over-confidence: (Farnam / Wikipedia) People tend to put a higher probability on desired events than undesired events. Most of us believe we are better performers, more honest and intelligent, have a better future, have a happier marriage, are less vulnerable than the average person, etc. But we can’t all be better than average.
• Hindsight Bias: (Farnam / Wikipedia) occurs when we look backward in time and see events are more predictable than they were at the time a decision was made.

Others

• Bias from incentives and reinforcement: (Farnam / Wikipedia) a consequence that will strengthen an organism's future behavior whenever that behavior is preceded by a specific antecedent stimulus. This strengthening effect may be measured as a higher frequency of behavior (e.g., pulling a lever more frequently), longer duration (e.g., pulling a lever for longer periods of time), greater magnitude (e.g., pulling a lever with greater force), or shorter latency (e.g., pulling a lever more quickly following the antecedent stimulus).
• Bias from self-interest: (Farnam / Wikipedia) generally refers to a focus on the needs or desires (interests) of the self over others.
• Bias from association: (Farnam / Wikipedia) in psychology refers to a connection between conceptual entities or mental states that result from the similarity between those states or their proximity in space or time.
• Bias from liking/loving: (Farnam / Wikipedia) humans ignore the faults and flaws of other people, products or companies if there is liking, love or admiration for them.
• Bias from disliking/hating: (Farnam / Wikipedia) We also ignore the virtues of those things we dislike and distort the facts to facilitate that hatred while putting on blinders to other options and opinions.
• Commitment and Consistency Bias: (Farnam / Wikipedia) Incorrectly remembering one's past attitudes and behavior as resembling present attitudes and behavior. [A] kind of built-in mechanism that makes us feel better after we make crappy decisions, especially at the cash register. Also known as Buyer’s Stockholm Syndrome, it’s a way of subconsciously justifying our purchases — especially expensive ones.
• Bias from excessive fairness: (Farnam / Wikipedia) Life isn’t fair, but many can’t accept this. Tolerating a little unfairness should be okay if it means a greater fairness for all. The example Munger uses is letting in other drivers on the freeway knowing they will reciprocate in the future.
• Bias from envy and jealousy: (Farnam / Wikipedia) having feelings of dislike and competitiveness with someone that is seen physically, or mentally better than yourself.
• Reciprocation bias: (Farnam / Wikipedia) a consequence that will strengthen an organism's future behavior whenever that behavior is preceded by a specific antecedent stimulus. This strengthening effect may be measured as a higher frequency of behavior (e.g., pulling a lever more frequently), longer duration (e.g., pulling a lever for longer periods of time), greater magnitude (e.g., pulling a lever with greater force), or shorter latency (e.g., pulling a lever more quickly following the antecedent stimulus).
• Over-influence from authority: (Farnam / Wikipedia) can be used to mean the right to exercise the power given by the State (in the form of government, judges, police officers, etc.), or by academic knowledge of an area (someone that can be an authority on a subject).
• Deprival Super-Reaction Bias: (Farnam / Wikipedia) When something we like is taken away or threatened to be taken away, we get upset. Taking away people’s freedom, status, money or anything they value will result in Deprival Super Reaction
• Bias from contrast: (Farnam / Source) The tendency to mentally upgrade or downgrade an object when comparing it to a contrasting object.
• Bias from stress-influence: (Farnam / Wikipedia) Adrenaline tends to produce faster and more extreme reactions. Some stress can improve performance but heavy stress often leads to dysfunction.
• Bias from emotional arousal: (Farnam / Source) Our everyday surroundings besiege us with information. The battle is for a share of our limited attention and memory, with the brain selecting the winners and discarding the losers. This can lead to making poor decisions.
• Bias from physical or psychological pain: (Farnam / Wikipedia) a specific subgroup of empathy that involves recognizing and understanding another person’s pain. Empathy is the mental ability that allows one person to understand another person’s mental and emotional state and how to effectively respond to that person. When a person receives cues that another person is in pain, neural pain circuits within the brain are activated.
• Fundamental Attribution Error: (Farnam / Wikipedia) the tendency for people to place an undue emphasis on internal characteristics (personality) to explain someone else's behavior in a given situation rather than considering the situation's external factors.
• Bias from the status quo: (Farnam / Wikipedia) a preference for the current state of affairs.
• Do something tendency: (Farnam / Wikipedia) People have a tendency to take action.
• Do nothing tendency: (Farnam / Wikipedia) Choice is often difficult, and decision makers may prefer to do nothing and ⁄ or to maintain their current course of action because it is easier. Status quo alternatives often require less mental effort to maintain
• Over-influence from precision/models: (Farnam / Wikipedia) Models are going to flawed and have exceptions. For example, economic models assume that consumers act rationally and we know that they often don't.
• Uncertainty avoidance: (Farnam / Wikipedia) a society's tolerance for uncertainty and ambiguity. It reflects the extent to which members of a society attempt to cope with anxiety by minimizing uncertainty.
• Not invented here bias: (Farnam / Wikipedia) a stance adopted by social, corporate, or institutional cultures that avoid using or buying already existing products, research, standards, or knowledge because of their external origins and costs.
• Short-term bias: (Farnam / Source) Some decisions must be made repeatedly and have consequences that change depending on how often each alternative is chosen. Such temporally extended decisions are pervasive and important, and often involve short-term/long-term tradeoffs.
• Tendency to avoid extremes: (Farnam / Wikipedia) being more likely to choose an option if it is the intermediate choice.
• Man with a Hammer Tendency: (Farnam / Wikipedia) an over-reliance on a familiar tool; as Abraham Maslow said in 1966, "I suppose it is tempting, if the only tool you have is a hammer, to treat everything as if it were a nail."
• Bias from social proof: (Farnam / Wikipedia) phenomenon where people assume the actions of others in an attempt to reflect correct behavior for a given situation. This effect is prominent in ambiguous social situations where people are unable to determine the appropriate mode of behavior and is driven by the assumption that surrounding people possess more knowledge about the situation.
• Over-influence from framing effects: (Farnam / Wikipedia) people react to a particular choice in different ways depending on how it is presented; e.g. as a loss or as a gain. People tend to avoid risk when a positive frame is presented but seek risks when a negative frame is presented. Gain and loss are defined in the scenario as descriptions of outcomes (e.g. lives lost or saved, disease patients treated and not treated, lives saved and lost during accidents, etc.).
• Lollapalooza: (Farnam / Wikipedia) for multiple biases, tendencies or mental models acting at the same time in the same direction. With the Lollapalooza effect, itself a mental model, the result is often extreme, due to the confluence of the mental models, biases or tendencies acting together, greatly increasing the likelihood of acting irrationally.
• List of additional Cognitive Biases

Business

• Price Sensitivity: (Farnam / Wikipedia / Investopedia) is the degree to which the price of a product affects consumers' purchasing behaviors. In economics, price sensitivity is commonly measured using the price elasticity of demand. For example, some consumers are not willing to pay even a few extra cents per gallon for gasoline, especially if a lower-priced station is nearby.
• Scale: (Farnam / Wikipedia) the capability of a system, network, or process to handle a growing amount of work or its potential to be enlarged in order to accommodate that growth.
• Distribution: (Farnam / Wikipedia) in economics refers to the way total output, income, or wealth is distributed among individuals or among the factors of production (such as labor, land, and capital).
• Cost: (Farnam / Wikipedia) the value of money that has been used up to produce something, and hence is not available for use anymore.
• Brand: (Farnam / Wikipedia) a set of marketing and communication methods that help to distinguish a company from competitors and create a lasting impression in the minds of customers.
• Improving Returns: (Farnam / Wikipedia) A performance measure used to evaluate the efficiency of an investment or to compare the efficiency of a number of different investments. ROI measures the amount of return on an investment relative to the investment’s cost. To calculate ROI, the benefit (or return) of an investment is divided by the cost of the investment, and the result is expressed as a percentage or a ratio.
• Porters 5 Forces: (Farnam / Wikipedia) a framework that attempts to analyze the level of competition within an industry and business strategy development. The forces include Threat of new entrants, Threat of substitutes, Bargaining power of buyers, Bargaining power of suppliers, Industry rivalry.  
• Decision Trees: (Farnam / Wikipedia) a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one way to display an algorithm.
• Diminishing Returns: (Farnam / Wikipedia) the decrease in the marginal (incremental) output of a production process as the amount of a single factor of production is incrementally increased, while the amounts of all other factors of production stay constant.
• Double Entry Accounting: (Farnam / Wikipedia) in accounting, is a system of bookkeeping so named because every entry to an account requires a corresponding and opposite entry to a different account. For instance, recording earnings of $100 would require making two entries: a debit entry of $100 to an account called "Cash" and a credit entry to an account called "Revenue."

Investing

• Mr. Market: (Farnam / Wikipedia) is an allegory created by investor Benjamin Graham. Graham asks the reader to imagine that he is one of the two owners of a business, along with a partner called Mr. Market. The partner frequently offers to sell his share of the business or to buy the reader's share. This partner is what today would be called manic-depressive, with his estimate of the business's value going from very pessimistic to wildly optimistic. The reader is always free to decline the partner's offer since he will soon come back with an entirely different offer.
• Circle of competence: (Farnam / Wikipedia) Each of us, through experience or study, has built up useful knowledge on certain areas of the world. Some areas are understood by most of us, while some areas require a lot more specialty to evaluate.

Ecology

• Complex adaptive systems: (Farnam / Wikipedia) a "complex macroscopic collection" of relatively "similar and partially connected micro-structures" formed in order to adapt to the changing environment and increase its survivability as a macro-structure. They are complex in that they are dynamic networks of interactions, and their relationships are not aggregations of the individual static entities. They are adaptive in that the individual and collective behavior mutate and self-organize corresponding to the change-initiating micro-event or collection of events.
• Systems Thinking: (Farnam / Wikipedia) involves the use of various techniques to study systems of many kinds. In nature, systems thinking examples include ecosystems in which various elements such as air, water, movement, plants, and animals work together to survive or perish. In organizations, systems consist of people, structures, and processes that work together to make an organization "healthy" or "unhealthy".

Economics

• Utility: (Farnam / Wikipedia) is a measure of preferences over some set of goods and services. The concept is an important underpinning of rational choice theory in economics and game theory because it represents satisfaction experienced by the consumer of a good.
• Diminishing Utility: (Farnam / Wikipedia) The concept that marginal utilities diminish across the ranges relevant to decision-making are called the "law of diminishing marginal utility" (and is also known as Gossen's First Law). This refers to the increase in utility and individual gains from increases in the consumption of a particular good.
• Supply and Demand: (Farnam / Wikipedia) an economic model of price determination in a market. It concludes that in a competitive market, the unit price for a particular good, or other traded item such as labor or liquid financial assets, will vary until it settles at a point where the quantity demanded (at the current price) will equal the quantity supplied (at the current price), resulting in an economic equilibrium for price and quantity transacted.
• Scarcity: (Farnam / Wikipedia) is the fundamental economic problem of having seemingly unlimited human wants in a world of limited resources. It states that society has insufficient productive resources to fulfill all human wants and needs.
• Elasticity: (Farnam / Wikipedia) the measurement of how responsive an economic variable is to a change in another. It gives answers to questions such as: If I lower the price of a product, how much more will sell? If I raise the price of one good, how will that affect sales of this other good? If the market price of a product goes down, how much will that affect the amount that firms will be willing to supply to the market? ‍
• Economies of Scale: (Farnam / Wikipedia) the cost advantages that enterprises obtain due to size, output, or scale of operation, with cost per unit of output generally decreasing with increasing scale as fixed costs are spread out over more units of output.‍
• Opportunity Cost: (Farnam / Wikipedia) the value of the best alternative forgone where, given limited resources, a choice needs to be made between several mutually exclusive alternatives. Assuming the best choice is made, it is the "cost" incurred by not enjoying the benefit that would have been had by taking the second best available choice.‍
• Marginal Cost: (Farnam / Wikipedia) the change in the total cost that arises when the quantity produced is incremented by one unit, that is, it is the cost of producing one more unit of a good.‍
• Comparative Advantage: (Farnam / Wikipedia) an economic theory about the work gains from trade for individuals, firms, or nations that arise from differences in their factor endowments or technological progress. In an economic model, an agent has a comparative advantage over another in producing a particular good if they can produce that good at a lower relative opportunity cost or autarky price, i.e. at a lower relative marginal cost prior to trade.‍
• Trade-offs: (Farnam / Wikipedia) a situation that involves losing one quality or aspect of something in return for gaining another quality or aspect. More colloquially, if one thing increases, some other thing must decrease.‍
• Price Discrimination: (Farnam / Wikipedia) a microeconomic pricing strategy where identical or largely similar goods or services are transacted at different prices by the same provider in different markets.‍
• Positive and Negative Externalities: (Farnam / Wikipedia) the cost or benefit that affects a party who did not choose to incur that cost or benefit. Economists often urge governments to adopt policies that "internalize" an externality, so that costs and benefits will affect mainly parties who choose to incur them.‍
• Sunk Costs: (Farnam / Wikipedia) a cost that has already been incurred and cannot be recovered. Sunk costs (also known as retrospective costs) are sometimes contrasted with prospective costs, which are future costs that may be incurred or changed if an action is taken.‍
• Moral Hazard: (Farnam / Wikipedia) occurs when one person takes more risks because someone else bears the cost of those risks. A moral hazard may occur where the actions of one party may change to the detriment of another after a financial transaction has taken place.‍
• Game Theory: (Farnam / Wikipedia / Source) What economists call game theory psychologists call the theory of social situations, which is an accurate description of what game theory is about. Although game theory is relevant to parlor games such as poker or bridge, most research in game theory focuses on how groups of people interact. There are two main branches of game theory: cooperative and noncooperative game theory. Noncooperative game theory deals largely with how intelligent individuals interact with one another in an effort to achieve their own goals. This is usually what people are referring to. ‍
• Prisoner's’ Dilemma: (Farnam / Wikipedia) a standard example of a game analyzed in game theory that shows why two completely "rational" individuals might not cooperate, even if it appears that it is in their best interests to do so. Two members of a criminal gang are arrested and imprisoned. Each prisoner is in solitary confinement with no means of communicating with the other. The prosecutors lack sufficient evidence to convict the pair on the principal charge. They hope to get both sentenced to a year in prison on a lesser charge. Simultaneously, the prosecutor's offer each prisoner a bargain. Each prisoner is given the opportunity either to: betray the other by testifying that the other committed the crime, or to cooperate with the other by remaining silent. The offer is: If A and B each betray the other, each of them serves 2 years in prison. If A betrays B but B remains silent, A will be set free and B will serve 3 years in prison (and vice versa). If A and B both remain silent, both of them will only serve 1 year in prison (on the lesser charge).‍
• Tragedy of the Commons: (Farnam / Wikipedia) an economic theory of a situation within a shared resource system where individual users acting independently according to their own self-interest behave contrary to the common good of all users by depleting that resource through their collective action.‍
• Bottlenecks: (Farnam / Wikipedia) one process in a chain of processes, such that its limited capacity reduces the capacity of the whole chain. The result of having a bottleneck are stalls in production, supply overstock, pressure from customers and low employee morale.‍
• Time value of Money: (Farnam / Wikipedia) describes the greater benefit of receiving money now rather than later. The principle of the time value of money explains why interest is paid or earned. Interest, whether it is a bank deposit or debt, compensates the depositor or lender for the time value of money.

Engineering

• Feedback loops: (Farnam / Wikipedia) Feedback loops are created when reactions affect themselves and can be positive or negative. Consider a thermostat regulating room temperature. This is an example of a negative feedback loop. As the temperature rises, the thermostat turns off the furnace allowing the room to rest at a predetermined temperature. When the temperature falls below that predetermined temperature the furnace reignites to return the room to its equilibrium state. Other examples include body temperature and financial markets.
• Redundancy: (Farnam / Wikipedia) We learn from Engineering that critical systems often require backup systems to guarantee a certain level of performance and minimize downtime. These systems are resilient to adverse conditions and if one fails there is spare capacity or a backup system.
• Margin of Safety: (Farnam / Wikipedia) basically says that if the part is loaded to the maximum load it should ever see in service, how many more loads of the same force can it withstand before failing. In effect, this is a measure of excess capacity.
• Tight coupling: (Farnam / Wikipedia / Source) tight coupling (or tightly coupled) is a type of coupling that describes a system in which hardware and software are not only linked together but are also dependent upon each other. In a tightly coupled system where multiple systems share a workload, the entire system usually would need to be powered down to fix a major hardware problem, not just the single system with the issue.
• Breakpoints: (Farnam / Wikipedia) is an intentional stopping or pausing place in a program, put in place for debugging purposes. It is also sometimes simply referred to as a pause.

Mathematics

• Bayes Theorem: (Farnam / Wikipedia) describes the probability of an event, based on conditions that might be related to the event. For example, suppose one is interested in whether a person has cancer, and knows the person's age. If cancer is related to age, then, using Bayes' theorem, information about the person's age can be used to more accurately assess the probability that they have cancer.
• Power Law: (Farnam / Wikipedia) a power law is a functional relationship between two quantities, where a relative change in one quantity results in a proportional relative change in the other quantity, independent of the initial size of those quantities: one quantity varies as a power of another.
• Law of large numbers: (Farnam / Wikipedia) describes the result of performing the same experiment a large number of times. According to the law, the average of the results obtained from a large number of trials should be close to the expected value, and will tend to become closer as more trials are performed.
• Compounding: (Farnam / Wikipedia / Source) Compounding is the ability of an asset to generate earnings, which are then reinvested in order to generate their own earnings. In other words, compounding refers to generating earnings from previous earnings.
• Probability Theory: (Farnam / Wikipedia) the analysis of random phenomena. The central objects of probability theory are random variables, stochastic processes, and events: mathematical abstractions of non-deterministic events or measured quantities that may either be single occurrences or evolve over time in an apparently random fashion.
• Permutations: (Farnam / Wikipedia) relates to the act of arranging all the members of a set into some sequence or order, or if the set is already ordered, rearranging (reordering) its elements, a process called permuting.
• Combinations: (Farnam / Wikipedia) a way of selecting items from a collection, such that (unlike permutations) the order of selection does not matter. In smaller cases, it is possible to count the number of combinations. For example, given three fruits, say an apple, an orange, and a pear, there are three combinations of two that can be drawn from this set: an apple and a pear; an apple and an orange; or a pear and an orange.
• Variability: (Farnam / Wikipedia / Source) The extent to which data points in a statistical distribution or data set diverge from the average or mean value. Variability also refers to the extent to which these data points differ from each other. There are four commonly used measures of variability: range, mean, variance and standard deviation.
• Standard Deviation: (Farnam / Wikipedia) a measure that is used to quantify the amount of variation or dispersion of a set of data values. A low standard deviation indicates that the data points tend to be close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the data points are spread out over a wider range of values.
• Normal Distribution (Farnam / Wikipedia) a function that represents the distribution of many random variables as a symmetrical bell-shaped graph.
• Regression to the mean: (Farnam / Wikipedia) the phenomenon that if a variable is extreme on its first measurement, it will tend to be closer to the average on its second measurement—and if it is extreme on its second measurement, it will tend to have been closer to the average on its first. To avoid making incorrect inferences, regression toward the mean must be considered when designing scientific experiments and interpreting data.
• Inversion: (Farnam / Wikipedia) it is in the nature of things that many hard problems are best solved when they are addressed backward. So what does this mean in practice? Spend less time trying to be brilliant and more time trying to avoid obvious stupidity. The kicker? Avoiding stupidity is easier than seeking brilliance.

Statistics

• Outliers: (Farnam / Wikipedia) an observation point that is distant from other observations. An outlier may be due to variability in the measurement or it may indicate experimental error; the latter are sometimes excluded from the data set.
• Self-Fulfilling Prophecy: (Farnam / Wikipedia) a prediction that directly or indirectly causes itself to become true, by the very terms of the prophecy itself, due to positive feedback between belief and behavior.
• Correlation versus Causation: (Farnam / Wikipedia) a phrase used in statistics to emphasize that a correlation between two variables does not imply that one causes the other. Many statistical tests calculate correlation between variables. A few go further, using correlation as a basis for testing a hypothesis of a true causal relationship.
• Mean: (Farnam / Wikipedia) measure of the central tendency either of a probability distribution or of the random variable characterized by that distribution.
• Median: (Farnam / Wikipedia) the value separating the higher half of a data sample, a population, or a probability distribution, from the lower half.
• Mode: (Farnam / Wikipedia) the value that appears most often in a set of data.
• Distribution: (Farnam / Wikipedia) the frequency of various outcomes in a sample.

Chemistry

• Thermodynamics: (Farnam / Wikipedia) the branch of science concerned with heat and temperature and their relation to energy and work. It states that the behavior of these quantities is governed by the four laws of thermodynamics, irrespective of the composition or specific properties of the material or system in question.
• Kinetics: (Farnam / Wikipedia) the study of rates of chemical processes. Chemical kinetics includes investigations of how different experimental conditions can influence the speed of a chemical reaction and yield information about the reaction's mechanism and transition states, as well as the construction of mathematical models that can describe the characteristics of a chemical reaction.
• Autocatalysis: (Farnam / Wikipedia) A single chemical reaction is said to have undergone autocatalysis, or be autocatalytic if one of the reaction products is also a reactant and therefore a catalyst in the same or a coupled reaction. The reaction is called an autocatalytic reaction.

Physics

• Newton’s Laws: (Farnam / Wikipedia) Newton's laws of motion are three physical laws that, together, laid the foundation for classical mechanics. They describe the relationship between a body and the forces acting upon it, and its motion in response to those forces. They have been expressed in several different ways, over nearly three centuries, and can be summarized as follows. First Law: When viewed in an inertial reference frame, an object either remains at rest or continues to move at a constant velocity unless acted upon by a net force. Second Law: In an inertial reference frame, the vector sum of the forces F on an object is equal to the mass m of that object multiplied by the acceleration vector a of the object: F = ma. Third Law: When one body exerts a force on a second body, the second body simultaneously exerts a force equal in magnitude and opposite in direction on the first body. ‍
• Momentum: (Farnam / Wikipedia) the product of the mass and velocity of an object. For example, a heavy truck moving rapidly has a large momentum—it takes a large or prolonged force to get the truck up to this speed, and it takes a large or prolonged force to bring it to a stop afterward. If the truck were lighter or moving more slowly, then it would have less momentum.‍
• Quantum Mechanics: (Farnam / Wikipedia / Source) Quantum mechanics is the branch of physics relating to the very small. It results in what may appear to be some very strange conclusions about the physical world. At the scale of atoms and electrons, many of the equations of classical mechanics, which describe how things move at everyday sizes and speeds, cease to be useful. In classical mechanics, objects exist in a specific place at a specific time. However, in quantum mechanics, objects instead exist in a haze of probability; they have a certain chance of being at point A, another chance of being at point B and so on.‍
• Critical Mass: (Farnam / Wikipedia) The term “critical mass” seems to have first appeared in nuclear physics. In this discipline, “critical mass” is the minimum amount of a given fissile material necessary to achieve a self-sustaining fission chain reaction. The term, however, is now used as a much broader construct. In astrophysics, for example, critical mass is a concept used to designate any mass that when exceeded causes something to happen. The concept of critical mass exists outside of physics and can easily be thought of as a tipping point. A Tipping Point, according to noted author Malcolm Gladwell in The Tipping Point: How Little Things Can Make a Big Difference, “is the moment of critical mass, the threshold, the boiling point.”‍
• Equilibrium: (Farnam / Wikipedia) Equilibrium is a balance between one or more opposing forces. As you can imagine, different types of equilibrium exist. Static equilibrium is when a system is at rest. Dynamic equilibrium is when two or more forces are equally matched.

Biology

• Natural Selection: (Farnam / Wikipedia) the differential survival and reproduction of individuals due to differences in phenotype. It is a key mechanism of evolution, the change in heritable traits of a population over time. Charles Darwin popularized the term "natural selection"; he compared it with artificial selection (selective breeding).

More Models:

• Asymmetric Information: (Farnam / Wikipedia) deals with the study of decisions in transactions where one party has more or better information than the other. This creates an imbalance of power in transactions, which can sometimes cause the transactions to go awry, a kind of market failure in the worst case.
• Occam’s Razor: (Farnam / Wikipedia) The principle can be interpreted as stating Among competing hypotheses, the one with the fewest assumptions should be selected.
• Deduction and Induction: (Farnam / Wikipedia:Inductive / Wikipedia:Deductive) Inductive reasoning involves drawing a conclusion by moving from specific observations to general ones. Deductive reasoning, on the other hand, involves drawing conclusions by applying a generalization to a specific example.
• Basic Decision Making Process: (Farnam / Wikipedia)regarded as the cognitive process resulting in the selection of a belief or a course of action among several alternative possibilities. Here is an example of one process: Work on the right problem. Identify all criteria. Create imaginative alternatives. Understand the consequences. Grapple with your tradeoffs. Clarify your uncertainties. Think hard about your risk tolerance. Consider linked decisions.‍
• Scientific Method: (Farnam / Wikipedia) a body of techniques for investigating phenomena, acquiring new knowledge, or correcting and integrating previous knowledge. To be termed scientific, a method of inquiry is commonly based on empirical or measurable evidence subject to specific principles of reasoning.

• Process versus Outcome: (Farnam / Wikipedia Outcome / Wikipedia Process / Source)
• Outcomes theory provides the conceptual basis for thinking about and working with outcomes systems of any type. An outcomes system is any system that: identifies; prioritizes; measures; attributes; or hold parties to account for outcomes of any type in any area.
• Process theory is a commonly used form of scientific research study in which events or occurrences are said to be the result of certain input states leading to a certain outcome (output) state, following a set process.
• And then what?: (Farnam / Wikipedia / Source) The ability to think beyond the “first step” and think through consequences. And then what?
• The Agency Problem: (Farnam / Wikipedia) (also known as agency dilemma or theory of agency) occurs when one person or entity (the "agent") is able to make decisions on behalf of, or that impact, another person or entity: the "principal".  This dilemma exists in circumstances where the agent is motivated to act in his own best interests, which are contrary to those of the principal, and is an example of moral hazard.
• 7 Deadly Sins: (Farnam / Wikipedia) The seven deadly sins, also known as the capital vices or cardinal sins, is a grouping and classification of vices. Behaviors or habits are classified under this category if they directly give birth to other immoralities. According to the standard list, they are hubristic pride, greed, lust, malicious envy, gluttony, inordinate anger, and sloth, which are also contrary to the seven virtues. These sins are often thought to be abuses of one's natural faculties or passions.
• Network Effect: (Farnam / Wikipedia) a network effect (also called network externality or demand-side economies of scale) is the effect that one user of a good or service has on the value of that product to other people. When a network effect is present, the value of a product or service is dependent on the number of others using it.
• Gresham’s Law: (Farnam / Wikipedia) a monetary principle stating that "bad money drives out good". For example, if there are two forms of commodity money in circulation, which are accepted by law as having similar face value, the more valuable commodity will disappear from circulation.
• The Red Queen Effect: (Farnam / Wikipedia) an evolutionary hypothesis which proposes that organisms must constantly adapt, evolve, and proliferate not merely to gain reproductive advantage, but also simply to survive while pitted against ever-evolving opposing organisms in an ever-changing environment, and intends to explain two different phenomena: the constant extinction rates as observed in the paleontological record caused by co-evolution between competing species, and the advantage of sexual reproduction (as opposed to asexual reproduction) at the level of individuals.

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