Statistical Analysis
Statistical modeling and testing
Multivariate Analysis & Dimensionality Reduction Prompt
Design a multivariate analysis that reduces high-dimensional data to interpretable structure — with method selection by analytical goal, component interpretation, and a validation framework that tests whether the reduced representation preserves the information that matters.
Distribution Fitting & Goodness-of-Fit Prompt
Fit the right probability distribution to your data — with candidate selection by data type and shape, goodness-of-fit testing, parameter estimation, and a business application that uses the fitted distribution for risk quantification and simulation.
Causal Inference Methods Prompt
Design a causal inference analysis that goes beyond correlation — with method selection by data structure and identification assumption, validity checks, and a results communication that correctly states what was and wasn't proven.
Sample Size & Statistical Power Analysis Prompt
Calculate the sample size your study actually needs — with power analysis tied to the minimum effect that matters, not the effect you expect to see, and a sensitivity table that shows how sample size changes with your assumptions.
Survival Analysis & Time-to-Event Modeling Prompt
Design a survival analysis that correctly handles censored observations, estimates survival curves by group, and interprets hazard ratios in business terms — not as abstract statistical quantities.
Bayesian Analysis & Inference Prompt
Design a Bayesian analysis that encodes prior knowledge correctly, produces posterior distributions that answer the actual business question, and communicates credible intervals in terms decision-makers can act on — not p-values in disguise.
Correlation Analysis & Interpretation Prompt
Run a correlation analysis that selects the right coefficient for the data type, tests significance correctly for multiple comparisons, and communicates what correlation does and does not imply — without the causation fallacy.
ANOVA & Variance Analysis Prompt
Design an ANOVA analysis that correctly handles multiple group comparisons — with assumption checks, post-hoc test selection, effect size calculation, and a results interpretation that tells you which groups differ and by how much.
Regression Analysis & Interpretation Prompt
Run and interpret a regression analysis that goes beyond R² — with coefficient interpretation in business terms, diagnostic checks for assumption violations, and a communication framework that explains what the model says and what it doesn't.
Hypothesis Testing Framework Prompt
Design a hypothesis testing framework that selects the right test for the data structure and question — with assumption checks, effect size calculation, and a results interpretation that distinguishes statistical significance from practical significance.