Distribution | Key Characteristics | Common Use Cases |
Normal (Gaussian) | Mean (μ) is typically 0, Standard Deviation (σ) is 1 | Regression, Anomaly Detection, Central Limit Theorem |
Uniform | All values in the range are equally likely | Random Sampling, Simulation, Monte Carlo Methods |
Bernoulli | Binary outcome (e.g., success or failure) | Binary Classification, A/B Testing |
Binomial | Number of successes in fixed trials (n) | Counting Successes/Failures, Probability Distributions |
Poisson | Number of events in a fixed interval (λ) | Count Data, Rare Event Modeling |
Exponential | Time between events in Poisson process (λ) | Survival Analysis, Reliability Engineering |
Log-Normal | Log of variable follows a Normal distribution | Modeling Positive Skewed Data |
Chi-Square | Hypothesis testing and confidence intervals (df) | Goodness of Fit Tests, Independence Tests |
Student's t-Distribution | Small sample sizes (df) | t-Tests, Confidence Intervals |
F-Distribution | Hypothesis testing, ANOVA (df1, df2) | Analysis of Variance (ANOVA), Regression Analysis |
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