Results for “skew-analysis”

Inspect, profile, clean, reconcile, analyze, visualize, and verify spreadsheet data while preserving formulas, formatting, types, and source files. Use when working with .xlsx, .xlsm, .xls, .ods, .csv, or .tsv files; answering questions from a workbook; auditing formulas or data quality; comparing sheets or versions; producing pivots, charts, forecasts, or summary workbooks; repairing malformed tables; or validating that spreadsheet edits and calculations are accurate.

Analyzes Zeek conn.log connection intervals using statistical methods to detect C2 beaconing patterns, flagging periodic connections with low jitter.

Analyze Zeek network logs to detect lateral movement techniques including SMB admin share access, DCE/RPC remote service creation, NTLM account spray, Kerberos anomalies, and large internal data transfers.

Estimate cell state transitions from unspliced/spliced mRNA dynamics using scVelo, infer trajectory directions, compute latent time, and identify driver genes in single-cell RNA-seq data.

Analyzes .NET project code coverage and CRAP (Change Risk Anti-Patterns) scores to identify risk hotspots, methods blocking coverage gains, and prioritize where to add tests.

Detect adversary lateral movement across networks using Splunk SPL queries against Windows authentication logs, SMB traffic, and remote service abuse.

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.

Analyze S&P 500 market breadth charts and CSV data to assess market health, identify trading signals, and generate positioning recommendations for different trader types.

Reduce SIEM alert fatigue by systematically tuning detection rules in Splunk and Elastic, using statistical baselines, whitelists, and precision/recall metrics.

Analyze RNA velocity in single-cell RNA-seq data with scVelo, estimating cell state transitions from unspliced/spliced mRNA dynamics, inferring trajectory directions, computing latent time, and identifying driver genes.

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

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