probabilities - Concepts

Explore concepts tagged with "probabilities"

Total concepts: 22

Concepts

Stochastic Processes - Mathematical models describing collections of random variables that evolve over time, used to model uncertainty in systems from finance to physics.
Statistical Significance - A measure of whether observed results are likely due to chance or represent a real effect.
Fat Tails - Probability distributions where extreme events occur more frequently than normal distributions predict.
Base Rate - The underlying probability of an event before considering specific evidence or conditions.
Luck and Success - The role of chance and circumstance in outcomes, and how to increase your luck surface area.
Bayes' Theorem - A mathematical framework for updating beliefs based on new evidence.
Law of Large Numbers - The principle that averages of random samples converge to expected values as sample size increases.
Monte Carlo Methods - Computational algorithms that use repeated random sampling to estimate numerical results, model complex systems, and solve problems that are deterministically intractable.
Probabilistic Thinking - Thinking in terms of likelihoods rather than certainties to make better decisions.
Central Limit Theorem - The principle that averages of random samples tend toward normal distribution regardless of underlying distribution.
Markov Chains - Mathematical systems that model sequences of events where the probability of each event depends only on the state of the previous event, not the full history.
Random Walk - A mathematical model describing a path consisting of successive random steps, used to model stock prices, particle diffusion, and many natural and social phenomena.
Expected Value - A probability-weighted average of all possible outcomes used to make rational decisions under uncertainty.
Ergodicity - Whether time averages equal ensemble averages - a crucial distinction for risk and decision-making.
Black Swan - A rare, unpredictable event with major impact that is rationalized in hindsight.
Regression to the Mean - Extreme outcomes tend to be followed by more moderate ones.
Small Sample Fallacy - The error of drawing strong conclusions from insufficient data.
Statistical Inference - The process of using data analysis and probability theory to draw conclusions about a population from a sample.
Power Law - A statistical distribution where small occurrences are extremely common and large occurrences extremely rare.
Normal Distribution - The bell curve pattern where most values cluster around the mean with symmetric tails.
Conservatism Bias - The tendency to insufficiently revise beliefs when presented with new evidence.
Insensitivity to Sample Size - The cognitive bias where people fail to adequately account for sample size when assessing the reliability of statistical information, treating small and large samples as equally informative.

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