Statistics/Probability Image
  1. Antifragile/Robustness (243) - Systems or entities that benefit from disorder or shocks, becoming stronger or more resilient in the face of adversity.
  2. Bayes' Theorem (244) - A mathematical theorem describing how to update probabilities based on new evidence or information.
  3. Black Swan Event (245) - Rare and unpredictable events with significant impact, often overlooked in traditional statistical models.
  4. Central Limit Theorem (246) - The principle that the distribution of sample means approaches a normal distribution as sample size increases.
  5. Clustering Illusion (247) - Perceiving patterns or clusters in random data where none actually exist, due to the human tendency to find order.
  6. Conditional Probability (248) - The probability of an event occurring given that another event has already occurred.
  7. Confidence Interval (249) - A range of values around an estimate that is likely to contain the true value with a certain level of confidence.
  8. Confounding Factor (250) - An extraneous variable that affects the relationship between the independent and dependent variables in a study.
  9. Correlation & Causation (251) - Correlation between two variables does not imply causation, as other factors may be influencing the relationship.
  10. Data Dredging (252) - Mining large datasets to find patterns or relationships, often leading to false discoveries due to multiple comparisons.
  11. Distributions (253) - Mathematical functions that describe the probability of various outcomes in a sample space.
  12. Error Bars (254) - Graphical representations showing the variability or uncertainty in a measurement or estimate.
  13. Expected Value (255) - The long-term average or mean outcome of a random variable, weighted by its probability of occurrence.
  14. False Negative (256) - Incorrectly concluding that something did not happen when it actually did (Type II error).
  15. False Positive (257) - Incorrectly concluding that something happened when it actually did not (Type I error).
  16. Fat-Tailed Distributions (258) - Probability distributions with higher probabilities of extreme events or outliers compared to a normal distribution.
  17. Forcing Function (259) - An event or factor that directly influences or drives a particular outcome or behavior.
  18. Game Theory (260) - The study of strategic decision-making among rational actors, often used in economics and political science.
  19. Law of Large Numbers (261) - The principle that the average of a large number of independent trials will converge to the true expected value.
  20. Mean/Median/Mode (262) - Measures of central tendency in a dataset representing, respectively, the average, middle value, and most frequent value.
  21. Meta Analyses (263) - Statistical analysis that combines the results of multiple studies to provide a more comprehensive overview.
  22. Monte Carlo Simulation (264) - Computational techniques using random sampling to model and analyze complex systems or processes.
  23. Normal Distribution (265) - A symmetric probability distribution characterized by its bell-shaped curve, often used in statistical analyses.
  24. Null Hypothesis (266) - The default assumption in hypothesis testing, suggesting that there is no significant difference or effect.
  25. P-Values (267) - The probability of obtaining results at least as extreme as those observed, assuming the null hypothesis is true.
  26. Power Law (268) - A mathematical relationship between two quantities where a relative change in one quantity results in a proportional change in the other.
  27. Probability Distribution (269) - A mathematical function that assigns probabilities to the possible outcomes of a random variable.
  28. Randomized Controlled Experiments (270) - Experimental studies where participants are randomly assigned to treatment and control groups to test interventions.
  29. Randomness (271) - Lack of pattern or predictability in events, outcomes, or data.
  30. Regression to the Mean (272) - The tendency for extreme values or outcomes to move closer to the average or mean over repeated trials or observations.
  31. Standard Deviation (273) - A measure of the dispersion or variability of a dataset, indicating the average deviation of data points from the mean.
  32. Statistical Significance (274) - The likelihood that an observed result is not due to chance variation, often measured using p-values or confidence intervals.
  33. Super Forecasters (275) - Individuals or groups with exceptional predictive accuracy, often in fields such as economics or geopolitics.
  34. Variance (276) - A measure of the spread or dispersion of data points around the mean in a dataset.