Statistical Strategy & Validation

Good decisions rest on numbers people can trust. We design sampling plans, sample sizes and analysis methods using R, Python, Stata and SPSS.

For impact questions, we apply methods such as difference-in-differences, propensity score matching and regression analysis, and we validate results through data quality checks, sensitivity analysis and model testing.

Most importantly, we help you understand what the numbers really mean, so your results stand firm when donors, regulators or reviewers ask hard questions.