Foundations of statistical reasoning
Build probability, estimation, uncertainty, testing, and study-design foundations in order.
Prerequisite map
Learn in a deliberate order.
Six paths turn the reference library into a curriculum. Begin at your current level; each sequence moves from concepts to defensible application.
Designing biological experiments
Move from the estimand and experimental unit to factorial, crossover, equivalence, and power-aware designs.
Regression and hierarchical modeling
Learn outcome models, diagnostics, correlated data, partial pooling, and robust alternatives.
Time, survival, and stochastic processes
Respect serial dependence, censoring, competing events, latent states, frequency structure, and spatial dependence.
Causal inference and evidence synthesis
Separate association from intervention effects, then combine evidence transparently across studies.
Statistics for imaging and computer vision
Connect measurement systems, nested bioimages, spatial objects, model evaluation, calibration, and deployment monitoring.