Results for “statistical-analysis”
7 skills
cloudthinker-ai managing-eppo
Manage feature flags, experiments, and metrics in Eppo via its REST API, including flag configuration, experiment design, statistical analysis, and metric pipelines.
7
ichichuang research-paper-writing
End-to-end pipeline for writing ML/AI research papers — from experiment design through analysis, drafting, revision, and submission. Covers NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Integrates automated experiment monitoring, statistical analysis, iterative writing, and citation verification.
0 · bundle
mukul975 detecting-data-and-model-poisoning
Detect poisoned training data and backdoored models across the ML pipeline using statistical analysis, activation clustering, and spectral signatures.
24.6k · bundle
More results
mukul975 analyzing-api-gateway-access-logs
Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts using pandas for statistical analysis and anomaly detection.
24.6k · bundle
chimeranext static-analysis
Configures and runs static analysis and linting tools across multiple languages, integrating with CI/CD and security platforms.
4
brycewang-stanford full-empirical-analysis-skill
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest + rdrobust + econml + causalml + matplotlib/seaborn. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) — every run produces a publication-ready output set with a multi-column regression table (M1→M6 progressive controls/FE) as the centerpiece, plus Table 1 (descriptives), mechanism / heterogeneity / robustness tables, and event-study + coefficient + trend figures. Covers the full 8-step pipeline an applied economist or quantitative social scientist runs on every paper — (1) data cleaning, (2) variable construction & transformation, (3) descriptive statistics & Table 1, (4) statistical diagnostic tests, (5) baseline empirical modeling, (6) robustness battery, (7) further analysis (mechanism, heterogeneity, mediation, moderation), (8) publication-ready tables & figures. **Also covers two parallel domain modes that share the same 8-step scaf
1k · bundle
theheavenlyd3mon qa-methodology
Design and apply QA methodology for software teams: test strategy, regression testing, CI failure triage, test automation, quality gates and metrics, risk-based testing, exploratory testing, test design techniques, AI code quality gates (independent verification, acceptance-criteria testability review for agentic Spec-Driven Development), mutation-guided test hardening and review evidence (surviving mutants, weak assertions, diff-aware mutation testing), agentic eval design (dataset test design, judge-as-system-under-test, flaky-eval discipline), QA career levels (Senior/Staff/Principal), and SDET engineering (test infrastructure, gTAA, CI/CD integration). Do not use for root-cause debugging of production incidents, security implementation or threat modeling, or evaluation framework governance and statistical analysis — route those to systematic-debugging, secure-software-engineering, and agent-evals-and-observability respectively.
28 · bundle