Results for “bias-analysis”

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

Guide through a structured data analysis workflow: define the question, validate data quality, select the appropriate analytical method, and produce decision-ready findings with caveats.

Design and evaluate paid-ad experiments with hypotheses, randomization, sample-size calculations, guardrails, and decision rules for A/B and split tests.

Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations.

Analiza datasets con Pandas y NumPy: explora distribuciones, correlaciones y patrones, y aplica tests de hipótesis para extraer conocimiento no obvio.

Reimplements DnaSP 6 for population genetics analysis of aligned DNA sequences, including nucleotide diversity, haplotype statistics, neutrality tests, linkage disequilibrium, recombination, mismatch distribution, InDel polymorphism, between-population divergence, outgroup-based tests, HKA test, McDonald-Kreitman.