Services
Statistical Analysis & Causal Inference Consulting
Apply PhD-level statistical rigor to measure business impact and eliminate selection bias. Expert in propensity score matching, difference-in-differences, and experimental design.
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Proven Methodology
- •Propensity Score Matching (PSM) - Create valid control groups by matching on observable characteristics
- •Difference-in-Differences (DiD) - Isolate treatment effects from time trends and unobserved confounders
- •Bootstrap Confidence Intervals - Provide robust uncertainty quantification for business decisions
- •Cluster-Based Analysis - Identify heterogeneous treatment effects across segments
- •Multiple Validation Methods - Placebo tests, sensitivity analysis, robustness checks
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Deliverables
- •Statistical analysis reports with transparent methodology
- •Executive presentations with business recommendations
- •Validated impact metrics with confidence intervals
- •Reusable analysis frameworks
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Tools & Platforms
- •Python (pandas, numpy, scipy, scikit-learn)
- •R (tidyverse, advanced modeling)
- •Statsmodels
- •PostgreSQL
- •AWS Secrets Manager
Engagement Options
Flexible consulting models tailored to your organization:
- • Strategic advisory retainers
- • End-to-end implementation projects
- • Team enablement and training programs
- • Fractional data & ML leadership
Featured Case Study
Explore how this service delivered measurable outcomes.
Ready to get started with Statistical Analysis & Causal Inference Consulting?
Schedule a consultation to discuss goals, scope, and the impact we can create together.