Results for “statistical-power”

Guides statistical hypothesis testing with assumption checks, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting for research data.

Guía para elegir y aplicar tests de hipótesis con SciPy, verificando supuestos, interpretando p-values y tamaño del efecto, y evitando falsos positivos.

Provides statistical process control guidance including control chart selection, capability indices, and out-of-control rules for quality management.

Compute the Kruskal-Wallis H-test using scipy.stats.kruskal for independent samples, returning the H statistic and p-value.

Analyze sprint data with Python scripts for velocity forecasting, health scoring, and retrospective insights to coach agile teams.

Build and optimize Power BI semantic models with star schema design, DAX measures, relationships, and row-level security following Microsoft best practices.

Guides setting up A/B tests with mandatory gates for hypothesis, metrics, and execution readiness.