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.