statistics - Concepts
Explore concepts tagged with "statistics"
Total concepts: 28
Concepts
- Base Rate Neglect - The tendency to ignore general statistical information in favor of specific case details when making judgments.
- Base Rate - The underlying probability of an event before considering specific evidence or conditions.
- Bayes' Theorem - A mathematical framework for updating beliefs based on new evidence.
- Central Limit Theorem - The principle that averages of random samples tend toward normal distribution regardless of underlying distribution.
- Clustering Illusion - Seeing patterns in random data, such as 'hot streaks' in random sequences.
- Confidence Interval - A range of values that likely contains the true population parameter with a specified probability.
- Correlation vs Causation - The critical distinction between two things occurring together and one actually causing the other.
- Effect Size - A measure of the magnitude or practical importance of a finding, independent of sample size.
- Ergodicity - Whether time averages equal ensemble averages - a crucial distinction for risk and decision-making.
- Failure Rate - The proportion of attempts that result in failure, used to calibrate expectations and strategies.
- Fat Tails - Probability distributions where extreme events occur more frequently than normal distributions predict.
- Hot-Hand Fallacy - Believing that a person who has experienced success has a greater chance of further success.
- Law of Large Numbers - The principle that averages of random samples converge to expected values as sample size increases.
- Long Tail Distribution - A distribution where many low-frequency items collectively represent significant aggregate value.
- Mean, Median, and Mode - Three different measures of central tendency, each useful in different contexts.
- Normal Distribution - The bell curve pattern where most values cluster around the mean with symmetric tails.
- Power Law - A statistical distribution where small occurrences are extremely common and large occurrences extremely rare.
- Regression to the Mean - Extreme outcomes tend to be followed by more moderate ones.
- Representativeness Heuristic - Judging probability by similarity to prototypes rather than by actual statistical likelihood.
- Sample Size - The number of observations in a study, critical for the reliability and precision of findings.
- Selection Bias - Distortion in analysis caused by non-random sampling or systematic exclusion of data.
- Signal vs Noise - Distinguishing meaningful patterns from random variation or irrelevant information.
- Simpson's Paradox - A phenomenon where trends in aggregated data reverse when data is separated into subgroups.
- Small Sample Fallacy - The error of drawing strong conclusions from insufficient data.
- Standard Deviation - A measure of how spread out values are from the mean.
- Statistical Significance - A measure of whether observed results are likely due to chance or represent a real effect.
- Type I and Type II Errors - False positives (detecting an effect that isn't there) and false negatives (missing an effect that exists).
- Variance - A measure of the spread of values, calculated as the average squared deviation from the mean.
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