Statistics MCP Servers

A marketing team asked an AI to analyze campaign data. The AI reported 'significant correlation between email frequency and purchase rate (p<0.05).' The team tripled emails. Unsubscribes spiked 340%. Sample: N=47 self-selected respondents, no power analysis. Correlation: observational, no confounders. Distribution: right-skewed but mean used. p=0.043 but Cohen's d=0.12. Trivial. Chart: truncated Y-axis making a 2% difference look enormous. This tool forces five axes: sample validity, causal inference, distribution awareness, significance with effect size, and visualization integrity.

Calculate item drop probabilities, pity mechanics, and expected resource usage for loot-based systems.

Calculate asset volatility sensitivity, Jensen's Alpha, and risk classification relative to market benchmarks.

Statistical simulation engine for evaluating D&D attribute generation methods.

Calculate full probability distributions, statistical metrics, and success thresholds for any dice notation.

Calculate required sample size, test duration, and peeking risk for A/B experiments.

Calculate statistical significance, p-values, and uplift for A/B tests.

Quantify conversion probability, expected loss, and uplift using Bayesian inference.

Perform 2k factorial analysis to identify optimal element combinations and interaction effects in multivariate experiments.

Calculate required A/B test duration, sample sizes, and experiment risk levels.