Results for “statistical-analysis”

Identify command-and-control beaconing patterns in network traffic by applying statistical frequency analysis, jitter calculation, and coefficient of variation scoring to detect periodic callbacks from compromised endpoints.

Analyzes uploaded data files with full Python access, producing cleaned datasets, statistical reports, charts, and dashboards via the CellCog coding agent.

Applies quantitative and qualitative analysis techniques, interprets experimental data, validates procedures, and selects appropriate methods with uncertainty quantification.

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.

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

Designs and backtests systematic trading strategies using technical indicators, fundamental analysis, and statistical models, with clear entry/exit rules, risk controls, and documentation.

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

Analiza series temporales: tendencia, estacionalidad y pronóstico con Prophet, statsmodels y ML, incluyendo descomposición, tests de estacionariedad y evaluación contra baselines.

Cleans datasets, detects anomalies, generates reports, and creates visualizations using pandas, scikit-learn, and plotting libraries to turn raw data into client-ready deliverables.

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

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

Performs financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making using financial statements and spreadsheet data.

Write, review, debug, or interpret Python statistical models using statsmodels, including formulas, regression, GLM, time series, robust covariance, diagnostics, prediction intervals, and inference.

Analyzes sector rotation patterns and market cycle positioning using publicly available CSV data, with optional chart image analysis.

Calculate sample sizes, minimum detectable effects, and power curves for study planning using closed-form formulas or Monte Carlo simulation.

Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data.

Performs differential expression analysis on label-free quantitative (LFQ) proteomics data from MaxQuant and DIA-NN outputs, including preprocessing, imputation, statistical testing, and visualization.

Generate professional clinical decision support documents for pharmaceutical and clinical research, including biomarker-stratified cohort analyses and evidence-based treatment recommendation reports with GRADE grading, statistical analysis, and publication-ready LaTeX/PDF output.

Build network traffic baselines from NetFlow/IPFIX data using Python pandas for statistical analysis, z-score anomaly detection, and hourly/daily traffic pattern profiling.

Detect anomalous user activities including impossible travel, unusual access patterns, privilege abuse, and insider threats using SIEM-based behavioral baselines and statistical analysis.

Parse Apache and Nginx access logs to detect SQL injection, LFI, XSS, scanner fingerprints, and brute-force patterns using regex-based detection, GeoIP enrichment, and statistical anomaly analysis.

Detects credential stuffing attacks by analyzing authentication logs for login velocity anomalies, ASN diversity, password spray patterns, and geographic distribution of failed logins using statistical analysis on Splunk or raw log data.