Analysis That Survives Technical Review
StatForge provides study design, quantitative analysis and defensible interpretation to research agencies, universities, evaluation firms and industrial clients — where a result has to hold up under peer review, regulatory scrutiny, or a board decision.
Capabilities
Senior-level quantitative work, from measurement through to interpretation.
Research design and measurement
Study design, sampling and weighting, survey and instrument structure, scale validation, power and sample size.
Modelling and econometrics
Regression, panel and time-series methods, structural equation modelling, choice and pricing models, segmentation, driver analysis, causal inference.
Uncertainty and defensibility
Diagnostics, robustness, error structure and confidence bounds, and methodology written to withstand adversarial technical review.
Who we work with
Research agencies
Analytical capacity behind fieldwork — weighting, modelling and reporting your clients can interrogate.
Universities and research institutes
Methods and estimation support for funded projects and peer-reviewed outputs.
Evaluation and impact firms
Identification strategy, estimation and reporting for impact and performance evaluations.
Energy and industrial clients
Demand, pricing and operational analytics where the number ends up in a regulatory or board pack.
Curtailment & grid riskCurtailment and grid risk on the Cape corridors
For wind and solar projects and the lenders behind them, we run hourly, scenario-based curtailment models over 32 years of measured weather — producing distributions of energy loss, revenue and debt cover rather than a single assumed percentage.
From the report
20.3%
Corridor-wide wind curtailment in a typical 2028 year if capacity stays where it is
R122m
Revenue span from contract mechanics alone — against roughly R19m from weather
What you receive
Concrete deliverables — not vague “analysis done” claims
Methodology memo
A written account of method choice, assumptions, identification, limitations and how each was addressed — the document a technical reviewer will ask for.
Report-ready tables, figures and models
Clean, labelled outputs and estimated models that drop straight into your report, publication or client deck.
Reproducible code and a documented analysis dataset
R or Python scripts and a documented analysis dataset, so every figure can be traced back to source data and re-run independently.
Engagement formats
Three ways to bring in analytical capacity, depending on how the work is shaped.
Scoped project
Defined deliverable, fixed fee.
- Agreed scope, deliverables and timeline before work starts
- Methodology memo, models and report-ready outputs
- Reproducible code and documented analysis dataset
Fees quoted per engagement.
Retained capacity
Day rate, for overflow work.
- Reserved capacity across a period you define
- Suited to peak periods and multiple parallel studies
- Works inside your own templates and reporting standards
- White-label by default — NDA signed, and the work is delivered under your name.
Fees quoted per engagement.
Technical review
Independent review of an existing analysis or model.
- Specification, assumptions and identification assessed
- Replication of headline results where data allows
- Written opinion on defensibility, with material risks ranked
Fees quoted per engagement.
Request a Proposal
Tell us about the work. We respond with scope, method, deliverables and timeline.
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